Implementation of the Multiple Intelligences Theory in the 21st Century Teaching and Learning Environments: A New Tool for Effective Teaching and Learning in All Levels.

ERIC Educational Resources Information Center

Mbuva, James

This paper focuses on the implementation of the multiple intelligences (MI) theory in 21st century teaching and learning environment, suggesting that it offers a new tool for effective teaching and learning at all levels. The eight current MI include: verbal/linguistic, logical/mathematical, visual/spatial, bodily/kinesthetic, musical/rhythmic,…

Innovative Socio-Technical Environments in Support of Distributed Intelligence and Lifelong Learning

ERIC Educational Resources Information Center

Fischer, G; Konomi, S.

2007-01-01

Individual, unaided human abilities are constrained. Media have helped us to transcend boundaries in thinking, working, learning and collaborating by supporting "distributed intelligence". Wireless and mobile technologies provide new opportunities for creating novel socio-technical environments and thereby empowering humans, but not without…

Structural Identification and Comparison of Intelligent Mobile Learning Environment

ERIC Educational Resources Information Center

Upadhyay, Nitin; Agarwal, Vishnu Prakash

2007-01-01

This paper proposes a methodology using graph theory, matrix algebra and permanent function to compare different architecture (structure) design of intelligent mobile learning environment. The current work deals with the development/selection of optimum architecture (structural) model of iMLE. This can be done using the criterion as discussed in…

Intelligent control based on fuzzy logic and neural net theory

NASA Technical Reports Server (NTRS)

Lee, Chuen-Chien

1991-01-01

In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment.

Multi-Agent Framework for Virtual Learning Spaces.

ERIC Educational Resources Information Center

Sheremetov, Leonid; Nunez, Gustavo

1999-01-01

Discussion of computer-supported collaborative learning, distributed artificial intelligence, and intelligent tutoring systems focuses on the concept of agents, and describes a virtual learning environment that has a multi-agent system. Describes a model of interactions in collaborative learning and discusses agents for Web-based virtual…

AI Based Personal Learning Environments: Directions for Long Term Research. AI Memo 384.

ERIC Educational Resources Information Center

Goldstein, Ira P.; Miller, Mark L.

The application of artificial intelligence (AI) techniques to the design of personal learning environments is an enterprise of both theoretical and practical interest. In the short term, the process of developing and testing intelligent tutoring programs serves as a new experimental vehicle for exploring alternative cognitive and pedagogical…

OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

NASA Astrophysics Data System (ADS)

Pedrazzoli, Attilio

2010-06-01

AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

Individual Differences in Learning from an Intelligent Discovery World: Smithtown.

ERIC Educational Resources Information Center

Shute, Valerie J.

"Smithtown" is an intelligent computer program designed to enhance an individual's scientific inquiry skills as well as to provide an environment for learning principles of basic microeconomics. It was hypothesized that intelligent computer instruction on applying effective interrogative skills (e.g., changing one variable at a time…

Learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.

2003-10-01

Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A mathematical model of the creative control process is presented that illustrates the use for mobile robots. Examples from a variety of intelligent mobile robot applications are also presented. The significance of this work is in providing a greater understanding of the applications of learning to mobile robots that could lead to many applications.

E-learning environment as intelligent tutoring system

NASA Astrophysics Data System (ADS)

Nagyová, Ingrid

2017-07-01

The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.

Not All Wizards Are from Oz: Iterative Design of Intelligent Learning Environments by Communication Capacity Tapering

ERIC Educational Resources Information Center

Mavrikis, Manolis; Gutierrez-Santos, Sergio

2010-01-01

This paper presents a methodology for the design of intelligent learning environments. We recognise that in the educational technology field, theory development and system-design should be integrated and rely on an iterative process that addresses: (a) the difficulty to elicit precise, concise, and operationalized knowledge from "experts" and (b)…

Encouraging Student Reflection and Articulation Using a Learning Companion: A Commentary

ERIC Educational Resources Information Center

Goodman, Bradley; Linton, Frank; Gaimari, Robert

2016-01-01

Our 1998 paper "Encouraging Student Reflection and Articulation using a Learning Companion" (Goodman et al. 1998) was a stepping stone in the progression of learning companions for intelligent tutoring systems (ITS). A simulated learning companion, acting as a peer in an intelligent tutoring environment ensures the availability of a…

Artificial intelligent e-learning architecture

NASA Astrophysics Data System (ADS)

Alharbi, Mafawez; Jemmali, Mahdi

2017-03-01

Many institutions and university has forced to use e learning, due to its ability to provide additional and flexible solutions for students and researchers. E-learning In the last decade have transported about the extreme changes in the distribution of education allowing learners to access multimedia course material at any time, from anywhere to suit their specific needs. In the form of e learning, instructors and learners live in different places and they do not engage in a classroom environment, but within virtual universe. Many researches have defined e learning based on their objectives. Therefore, there are small number of e-learning architecture have proposed in the literature. However, the proposed architecture has lack of embedding intelligent system in the architecture of e learning. This research argues that unexplored potential remains, as there is scope for e learning to be intelligent system. This research proposes e-learning architecture that incorporates intelligent system. There are intelligence components, which built into the architecture.

Learning from Multiple Collaborating Intelligent Tutors: An Agent-based Approach.

ERIC Educational Resources Information Center

Solomos, Konstantinos; Avouris, Nikolaos

1999-01-01

Describes an open distributed multi-agent tutoring system (MATS) and discusses issues related to learning in such open environments. Topics include modeling a one student-many teachers approach in a computer-based learning context; distributed artificial intelligence; implementation issues; collaboration; and user interaction. (Author/LRW)

Research on Intelligent Synthesis Environments

NASA Technical Reports Server (NTRS)

Noor, Ahmed K.; Lobeck, William E.

2002-01-01

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

Research on Intelligent Synthesis Environments

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.; Loftin, R. Bowen

2002-12-01

Four research activities related to Intelligent Synthesis Environment (ISE) have been performed under this grant. The four activities are: 1) non-deterministic approaches that incorporate technologies such as intelligent software agents, visual simulations and other ISE technologies; 2) virtual labs that leverage modeling, simulation and information technologies to create an immersive, highly interactive virtual environment tailored to the needs of researchers and learners; 3) advanced learning modules that incorporate advanced instructional, user interface and intelligent agent technologies; and 4) assessment and continuous improvement of engineering team effectiveness in distributed collaborative environments.

The Effect of Web Assisted Learning with Emotional Intelligence Content on Students' Information about Energy Saving, Attitudes towards Environment and Emotional Intelligence

ERIC Educational Resources Information Center

Ercan, Orhan; Ural, Evrim; Köse, Sinan

2017-01-01

For a sustainable world, it is very important for students to develop positive environmental attitudes and to have awareness of energy use. The study aims to investigate the effect of web assisted instruction with emotional intelligence content on 8th grade students' emotional intelligence, attitudes towards environment and energy saving, academic…

Energizing the nursing lecture: Application of the Theory of Multiple Intelligence Learning.

PubMed

Amerson, Roxanne

2006-01-01

Nurse educators struggle to find ways to create learning opportunities that are interactive and appeal to the needs of various students. The key to energizing the nursing lecture is to create an environment that encourages students to be active participants. It is essential to use creativity to design cognitive strategies that appeal to students' learning preferences. This article discusses the methods one educator has used to implement the Theory of Multiple Intelligence Learning in the classroom. Specific cognitive strategies that address the learning preferences of each intelligence are discussed.

The Impact of Integrated Coaching and Collaboration within an Inquiry Learning Environment

ERIC Educational Resources Information Center

Dragon, Toby

2013-01-01

This thesis explores the design and evaluation of a collaborative, inquiry learning Intelligent Tutoring System for ill-defined problem spaces. The common ground in the fields of Artificial Intelligence in Education and Computer-Supported Collaborative Learning is investigated to identify ways in which tutoring systems can employ both automated…

Integration of an Intelligent Tutoring System in a Course of Computer Network Design

ERIC Educational Resources Information Center

Verdú, Elena; Regueras, Luisa M.; Gal, Eran; de Castro, Juan P.; Verdú, María J.; Kohen-Vacs, Dan

2017-01-01

INTUITEL is a research project aiming to offer a personalized learning environment. The INTUITEL approach includes an Intelligent Tutoring System that gives students recommendations and feedback about what the best learning path is for them according to their profile, learning progress, context and environmental influences. INTUITEL combines…

Early prediction of student goals and affect in narrative-centered learning environments

NASA Astrophysics Data System (ADS)

Lee, Sunyoung

Recent years have seen a growing recognition of the role of goal and affect recognition in intelligent tutoring systems. Goal recognition is the task of inferring users' goals from a sequence of observations of their actions. Because of the uncertainty inherent in every facet of human computer interaction, goal recognition is challenging, particularly in contexts in which users can perform many actions in any order, as is the case with intelligent tutoring systems. Affect recognition is the task of identifying the emotional state of a user from a variety of physical cues, which are produced in response to affective changes in the individual. Accurately recognizing student goals and affect states could contribute to more effective and motivating interactions in intelligent tutoring systems. By exploiting knowledge of student goals and affect states, intelligent tutoring systems can dynamically modify their behavior to better support individual students. To create effective interactions in intelligent tutoring systems, goal and affect recognition models should satisfy two key requirements. First, because incorrectly predicted goals and affect states could significantly diminish the effectiveness of interactive systems, goal and affect recognition models should provide accurate predictions of user goals and affect states. When observations of users' activities become available, recognizers should make accurate early" predictions. Second, goal and affect recognition models should be highly efficient so they can operate in real time. To address key issues, we present an inductive approach to recognizing student goals and affect states in intelligent tutoring systems by learning goals and affect recognition models. Our work focuses on goal and affect recognition in an important new class of intelligent tutoring systems, narrative-centered learning environments. We report the results of empirical studies of induced recognition models from observations of students' interactions in narrative-centered learning environments. Experimental results suggest that induced models can make accurate early predictions of student goals and affect states, and they are sufficiently efficient to meet the real-time performance requirements of interactive learning environments.

Adaptive Intelligent Support to Improve Peer Tutoring in Algebra

ERIC Educational Resources Information Center

Walker, Erin; Rummel, Nikol; Koedinger, Kenneth R.

2014-01-01

Adaptive collaborative learning support (ACLS) involves collaborative learning environments that adapt their characteristics, and sometimes provide intelligent hints and feedback, to improve individual students' collaborative interactions. ACLS often involves a system that can automatically assess student dialogue, model effective and…

Scaffolding and Integrated Assessment in Computer Assisted Learning (CAL) for Children with Learning Disabilities

ERIC Educational Resources Information Center

Beale, Ivan L.

2005-01-01

Computer assisted learning (CAL) can involve a computerised intelligent learning environment, defined as an environment capable of automatically, dynamically and continuously adapting to the learning context. One aspect of this adaptive capability involves automatic adjustment of instructional procedures in response to each learner's performance,…

The Impact of Game-Like Features on Learning from an Intelligent Tutoring System

ERIC Educational Resources Information Center

Millis, Keith; Forsyth, Carol; Wallace, Patricia; Graesser, Arthur C.; Timmins, Gary

2017-01-01

Prior research has shown that students learn from Intelligent Tutoring Systems (ITS). However, students' attention may drift or become disengaged with the task over extended amounts of instruction. To remedy this problem, researchers have examined the impact of game-like features (e.g., a narrative) in digital learning environments on motivation…

Note-Taking within MetaTutor: Interactions between an Intelligent Tutoring System and Prior Knowledge on Note-Taking and Learning

ERIC Educational Resources Information Center

Trevors, Gregory; Duffy, Melissa; Azevedo, Roger

2014-01-01

Hypermedia learning environments (HLE) unevenly present new challenges and opportunities to learning processes and outcomes depending on learner characteristics and instructional supports. In this experimental study, we examined how one such HLE--MetaTutor, an intelligent, multi-agent tutoring system designed to scaffold cognitive and…

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

NASA Technical Reports Server (NTRS)

Chen, Alexander Y.

1990-01-01

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

An Analysis of Student Model Portability

ERIC Educational Resources Information Center

Valdés Aguirre, Benjamín; Ramírez Uresti, Jorge A.; du Boulay, Benedict

2016-01-01

Sharing user information between systems is an area of interest for every field involving personalization. Recommender Systems are more advanced in this aspect than Intelligent Tutoring Systems (ITSs) and Intelligent Learning Environments (ILEs). A reason for this is that the user models of Intelligent Tutoring Systems and Intelligent Learning…

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments.

PubMed

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

Learning of embodied interaction dynamics with recurrent neural networks: some exploratory experiments

NASA Astrophysics Data System (ADS)

Oubbati, Mohamed; Kord, Bahram; Koprinkova-Hristova, Petia; Palm, Günther

2014-04-01

The new tendency of artificial intelligence suggests that intelligence must be seen as a result of the interaction between brains, bodies and environments. This view implies that designing sophisticated behaviour requires a primary focus on how agents are functionally coupled to their environments. Under this perspective, we present early results with the application of reservoir computing as an efficient tool to understand how behaviour emerges from interaction. Specifically, we present reservoir computing models, that are inspired by imitation learning designs, to extract the essential components of behaviour that results from agent-environment interaction dynamics. Experimental results using a mobile robot are reported to validate the learning architectures.

E-Learning Agents

ERIC Educational Resources Information Center

Gregg, Dawn G.

2007-01-01

Purpose: The purpose of this paper is to illustrate the advantages of using intelligent agents to facilitate the location and customization of appropriate e-learning resources and to foster collaboration in e-learning environments. Design/methodology/approach: This paper proposes an e-learning environment that can be used to provide customized…

Cognitive Tools for Assessment and Learning in a High Information Flow Environment.

ERIC Educational Resources Information Center

Lajoie, Susanne P.; Azevedo, Roger; Fleiszer, David M.

1998-01-01

Describes the development of a simulation-based intelligent tutoring system for nurses working in a surgical intensive care unit. Highlights include situative learning theories and models of instruction, modeling expertise, complex decision making, linking theories of learning to the design of computer-based learning environments, cognitive task…

Multiple Intelligences to Promote Metacognition in the Online Learning Environment

ERIC Educational Resources Information Center

Stewart, Daniel P.

2013-01-01

This representative embedded study embraced hermeneutic qualitative methods and was grounded in the constructivist paradigm. The study explored how Howard Gardner's Theory of Multiple Intelligences (MI), promoted metacognition leading to self-efficacy in online learning. The number of colleges offering online courses has grown tremendously,…

A Group Intelligence-Based Asynchronous Argumentation Learning-Assistance Platform

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Chang, Shun-Chih; Chen, Heng-Ming; Tseng, Jhe-Hao; Chien, Sheng-Yuan

2016-01-01

Structured argumentation support environments have been built and used in scientific discourse in the literature. However, to the best our knowledge, there is no research work in the literature examining whether student's knowledge has grown during learning activities with asynchronous argumentation. In this work, an intelligent computer-supported…

A Multi-Agent System Approach for Distance Learning Architecture

ERIC Educational Resources Information Center

Turgay, Safiye

2005-01-01

The goal of this study is to suggest the agent systems by intelligence and adaptability properties in distance learning environment. The suggested system has flexible, agile, intelligence and cooperation features. System components are teachers, students (learners), and resources. Inter component relations are modeled and reviewed by using the…

An Intelligent System for Document Retrieval in Distributed Office Environments.

ERIC Educational Resources Information Center

Mukhopadhyay, Uttam; And Others

1986-01-01

MINDS (Multiple Intelligent Node Document Servers) is a distributed system of knowledge-based query engines for efficiently retrieving multimedia documents in an office environment of distributed workstations. By learning document distribution patterns and user interests and preferences during system usage, it customizes document retrievals for…

Intelligent Fuzzy Spelling Evaluator for e-Learning Systems

ERIC Educational Resources Information Center

Chakraborty, Udit Kr.; Konar, Debanjan; Roy, Samir; Choudhury, Sankhayan

2016-01-01

Evaluating Learners' Response in an e-Learning environment has been the topic of current research in areas of Human Computer Interaction, e-Learning, Education Technology and even Natural Language Processing. The current paper presents a twofold strategy to evaluate single word response of a learner in an e-Learning environment. The response of…

Theories of Intelligence, Learning, and Motivation as a Basis for Praxis

ERIC Educational Resources Information Center

Nderu-Boddington, Eulalee

2008-01-01

This paper examines how Piaget, Werner, and Gardner differ regarding the roles of cognition, intelligence, and learning in the developmental process. Piaget believes in the predominance of genetic factors. Werner stresses the influence of biological factors, while Gardner proposes that the environment plays a greater influence in how intelligence…

Authoring Tools for Collaborative Intelligent Tutoring System Environments

ERIC Educational Resources Information Center

Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol; Sewall, Jonathan; Ringenberg, Michael

2014-01-01

Authoring tools have been shown to decrease the amount of time and resources needed for the development of Intelligent Tutoring Systems (ITSs). Although collaborative learning has been shown to be beneficial to learning, most of the current authoring tools do not support the development of collaborative ITSs. In this paper, we discuss an extension…

The "Intelligent Classroom": Changing Teaching and Learning with an Evolving Technological Environment.

ERIC Educational Resources Information Center

Winer, Laura R.; Cooperstock, Jeremy

2002-01-01

Describes the development and use of the Intelligent Classroom collaborative project at McGill University that explored technology use to improve teaching and learning. Explains the hardware and software installation that allows for the automated capture of audio, video, slides, and handwritten annotations during a live lecture, with subsequent…

Fuzzy Q-Learning for Generalization of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

An intelligent agent for optimal river-reservoir system management

NASA Astrophysics Data System (ADS)

Rieker, Jeffrey D.; Labadie, John W.

2012-09-01

A generalized software package is presented for developing an intelligent agent for stochastic optimization of complex river-reservoir system management and operations. Reinforcement learning is an approach to artificial intelligence for developing a decision-making agent that learns the best operational policies without the need for explicit probabilistic models of hydrologic system behavior. The agent learns these strategies experientially in a Markov decision process through observational interaction with the environment and simulation of the river-reservoir system using well-calibrated models. The graphical user interface for the reinforcement learning process controller includes numerous learning method options and dynamic displays for visualizing the adaptive behavior of the agent. As a case study, the generalized reinforcement learning software is applied to developing an intelligent agent for optimal management of water stored in the Truckee river-reservoir system of California and Nevada for the purpose of streamflow augmentation for water quality enhancement. The intelligent agent successfully learns long-term reservoir operational policies that specifically focus on mitigating water temperature extremes during persistent drought periods that jeopardize the survival of threatened and endangered fish species.

Adaptive versus Learner Control in a Multiple Intelligence Learning Environment

ERIC Educational Resources Information Center

Kelly, Declan

2008-01-01

Within the field of technology enhanced learning, adaptive educational systems offer an advanced form of learning environment that attempts to meet the needs of different students. Such systems capture and represent, for each student, various characteristics such as knowledge and traits in an individual learner model. Subsequently, using the…

Intelligent mobility research for robotic locomotion in complex terrain

NASA Astrophysics Data System (ADS)

Trentini, Michael; Beckman, Blake; Digney, Bruce; Vincent, Isabelle; Ricard, Benoit

2006-05-01

The objective of the Autonomous Intelligent Systems Section of Defence R&D Canada - Suffield is best described by its mission statement, which is "to augment soldiers and combat systems by developing and demonstrating practical, cost effective, autonomous intelligent systems capable of completing military missions in complex operating environments." The mobility requirement for ground-based mobile systems operating in urban settings must increase significantly if robotic technology is to augment human efforts in these roles and environments. The intelligence required for autonomous systems to operate in complex environments demands advances in many fields of robotics. This has resulted in large bodies of research in areas of perception, world representation, and navigation, but the problem of locomotion in complex terrain has largely been ignored. In order to achieve its objective, the Autonomous Intelligent Systems Section is pursuing research that explores the use of intelligent mobility algorithms designed to improve robot mobility. Intelligent mobility uses sensing, control, and learning algorithms to extract measured variables from the world, control vehicle dynamics, and learn by experience. These algorithms seek to exploit available world representations of the environment and the inherent dexterity of the robot to allow the vehicle to interact with its surroundings and produce locomotion in complex terrain. The primary focus of the paper is to present the intelligent mobility research within the framework of the research methodology, plan and direction defined at Defence R&D Canada - Suffield. It discusses the progress and future direction of intelligent mobility research and presents the research tools, topics, and plans to address this critical research gap. This research will create effective intelligence to improve the mobility of ground-based mobile systems operating in urban settings to assist the Canadian Forces in their future urban operations.

Effects of Multiple Intelligences Supported Project-Based Learning on Students' Achievement Levels and Attitudes towards English Lesson

ERIC Educational Resources Information Center

Bas, Gökhan; Beyhan, Ömer

2010-01-01

The aim of the research was to investigate the effects of multiple intelligences supported project-based learning and traditional foreign language-teaching environment on students' achievement and their attitude towards English lesson. The research was carried out in 2009-2010 education-instruction year in Karatli Sehit Sahin Yilmaz Elementary…

Relationship between Students' Emotional Intelligence, Social Bond, and Interactions in Online Learning

ERIC Educational Resources Information Center

Han, Heeyoung; Johnson, Scott D.

2012-01-01

The purpose of the study was to investigate the relationship between students' emotional intelligence, social bond, and their interactions in an online learning environment. The research setting in this study was a 100% online master's degree program within a university located in the Midwest of the United States. Eighty-four students participated…

Social Web Content Enhancement in a Distance Learning Environment: Intelligent Metadata Generation for Resources

ERIC Educational Resources Information Center

García-Floriano, Andrés; Ferreira-Santiago, Angel; Yáñez-Márquez, Cornelio; Camacho-Nieto, Oscar; Aldape-Pérez, Mario; Villuendas-Rey, Yenny

2017-01-01

Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however, for this to happen, metadata needs to be present.…

The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement

NASA Astrophysics Data System (ADS)

Makahinda, T.

2018-02-01

The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

A Mindful Approach to Teaching Emotional Intelligence to Undergraduate Students Online and in Person

ERIC Educational Resources Information Center

Cotler, Jami L.; DiTursi, Dan; Goldstein, Ira; Yates, Jeff; DelBelso, Deb

2017-01-01

In this paper we examine whether emotional intelligence (EI) can be taught online and, if so, what key variables influence the successful implementation of this online learning model. Using a 3 x 2 factorial quasi-experimental design, this mixed-methods study found that a team-based learning environment using a blended teaching approach, supported…

A reflective framework to foster emotionally intelligent leadership in nursing.

PubMed

Heckemann, Birgit; Schols, Jos M G A; Halfens, Ruud J G

2015-09-01

To propose a reflective framework based on the perspective of emotional intelligence (EI) in nurse leadership literature. Emotional intelligence is a self-development construct aimed at enhancing the management of feelings and interpersonal relationships, which has become increasingly popular in nurse leadership. Reflection is an established means to foster learning. Integrating those aspects of emotional intelligence pertinent to nurse leadership into a reflective framework might support the development of nurse leadership in a practical context. A sample of 22 articles, retrieved via electronic databases (Ovid/Medline, BNI, psycArticles, Zetoc and CINAHL) and published between January 1996 and April 2009, was analysed in a qualitative descriptive content analysis. Three dimensions that characterise emotional intelligence leadership in the context of nursing - the nurse leader as a 'socio-cultural architect', as a 'responsive carer' and as a 'strategic visionary' - emerged from the analysis. To enable practical application, these dimensions were contextualised into a reflective framework. Emotional intelligence skills are regarded as essential for establishing empowering work environments in nursing. A reflective framework might aid the translation of emotional intelligence into a real-world context. The proposed framework may supplement learning about emotional intelligence skills and aid the integration of emotional intelligence in a clinical environment. © 2014 John Wiley & Sons Ltd.

Innovative intelligent technology of distance learning for visually impaired people

NASA Astrophysics Data System (ADS)

Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet

2017-12-01

The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV). To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.

Toward a Model for the Conceptual Understanding of Personal Learning Environments: A Case Study

ERIC Educational Resources Information Center

Ivanova, Malinka; Chatti, Mohamed Amine

2011-01-01

The development of Personal Learning Environments (PLEs) is in the scope of research groups and educators aiming to propose suitable mechanisms for the organization of self-controlled and self-directed learning, providing students with tools and services for access to content and human intelligence inside and outside the educational institutions.…

Exploring Relations among College Students' Prior Knowledge, Implicit Theories of Intelligence, and Self-Regulated Learning in a Hypermedia Environment

ERIC Educational Resources Information Center

Greene, Jeffrey Alan; Costa, Lara-Jeane; Robertson, Jane; Pan, Yi; Deekens, Victor M.

2010-01-01

Researchers and educators continue to explore how to assist students in the acquisition of conceptual understanding of complex science topics. While hypermedia learning environments (HLEs) afford unique opportunities to display multiple representations of these often abstract topics, students who do not engage in self-regulated learning (SRL) with…

Virtual Reality: The Future of Animated Virtual Instructor, the Technology and Its Emergence to a Productive E-Learning Environment.

ERIC Educational Resources Information Center

Jiman, Juhanita

This paper discusses the use of Virtual Reality (VR) in e-learning environments where an intelligent three-dimensional (3D) virtual person plays the role of an instructor. With the existence of this virtual instructor, it is hoped that the teaching and learning in the e-environment will be more effective and productive. This virtual 3D animated…

Accelerated Learning: Madness with a Method.

ERIC Educational Resources Information Center

Zemke, Ron

1995-01-01

Accelerated learning methods have evolved into a variety of holistic techniques that involve participants in the learning process and overcome negative attitudes about learning. These components are part of the mix: the brain, learning environment, music, imaginative activities, suggestion, positive mental state, the arts, multiple intelligences,…

The desktop interface in intelligent tutoring systems

NASA Technical Reports Server (NTRS)

Baudendistel, Stephen; Hua, Grace

1987-01-01

The interface between an Intelligent Tutoring System (ITS) and the person being tutored is critical to the success of the learning process. If the interface to the ITS is confusing or non-supportive of the tutored domain, the effectiveness of the instruction will be diminished or lost entirely. Consequently, the interface to an ITS should be highly integrated with the domain to provide a robust and semantically rich learning environment. In building an ITS for ZetaLISP on a LISP Machine, a Desktop Interface was designed to support a programming learning environment. Using the bitmapped display, windows, and mouse, three desktops were designed to support self-study and tutoring of ZetaLISP. Through organization, well-defined boundaries, and domain support facilities, the desktops provide substantial flexibility and power for the student and facilitate learning ZetaLISP programming while screening the student from the complex LISP Machine environment. The student can concentrate on learning ZetaLISP programming and not on how to operate the interface or a LISP Machine.

A State Cyber Hub Operations Framework

DTIC Science & Technology

2016-06-01

to communicate and sense or interact with their internal states or the external environment. Machine Learning: A type of artificial intelligence that... artificial intelligence , and computational linguistics concerned with the interactions between computers and human (natural) languages. Patching: A piece...formalizing a proof of concept for cyber initiatives and developed frameworks for operationalizing the data and intelligence produced across state

Learning Unknown Event Models

DTIC Science & Technology

2014-07-01

Intelligence (www.aaai.org). All rights reserved. knowledge engineering, but it is often impractical due to high environment variance, or unknown events...distribution unlimited 13. SUPPLEMENTARY NOTES In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 27-31 July 2014...autonomy for responding to unexpected events in strategy simulations. Computational Intelligence , 29(2), 187-206. Leake, D. B. (1991), Goal-based

Measure of Effectiveness for JSTARS Ground Moving Target Indicator: A Value Focused Thinking Approach

DTIC Science & Technology

2011-03-01

the dictionary state intelligence is the ability to learn or understand or deal with new or trying situations. It is also defined as the ability to...approach is most appropriate for a military organization as it is concerned with the “ability to learn and understand”, they are also interested in...knowledge on our enemy so that we have the ability to learn and understand them and ultimately defeat them. In the joint environment, intelligence is

A Measure of Real-Time Intelligence

NASA Astrophysics Data System (ADS)

Gavane, Vaibhav

2013-03-01

We propose a new measure of intelligence for general reinforcement learning agents, based on the notion that an agent's environment can change at any step of execution of the agent. That is, an agent is considered to be interacting with its environment in real-time. In this sense, the resulting intelligence measure is more general than the universal intelligence measure (Legg and Hutter, 2007) and the anytime universal intelligence test (Hernández-Orallo and Dowe, 2010). A major advantage of the measure is that an agent's computational complexity is factored into the measure in a natural manner. We show that there exist agents with intelligence arbitrarily close to the theoretical maximum, and that the intelligence of agents depends on their parallel processing capability. We thus believe that the measure can provide a better evaluation of agents and guidance for building practical agents with high intelligence.

The Teaching and Learning Environment SAIDA: Some Features and Lessons.

ERIC Educational Resources Information Center

Grandbastien, Monique; Morinet-Lambert, Josette

Written in ADA language, SAIDA, a Help System for Data Implementation, is an experimental teaching and learning environment which uses artificial intelligence techniques to teach a computer science course on abstract data representations. The application domain is teaching advanced programming concepts which have not received much attention from…

Narrative-Based Interactive Learning Environments from Modelling Reasoning

ERIC Educational Resources Information Center

Yearwood, John; Stranieri, Andrew

2007-01-01

Narrative and story telling has a long history of use in structuring, organising and communicating human experience. This paper describes a narrative based interactive intelligent learning environment which aims to elucidate practical reasoning using interactive emergent narratives that can be used in training novices in decision making. Its…

Environmental Education: Understanding the World around Us

ERIC Educational Resources Information Center

Bodor, Sarah

2016-01-01

Environmental education teaches children and adults how to learn about and investigate their environment and to make intelligent, informed decisions about how they can take care of it. It is taught in traditional classrooms, in communities, and in settings like nature centers, museums, parks, and zoos. Learning about the environment involves many…

Learning Analytics Platform, towards an Open Scalable Streaming Solution for Education

ERIC Educational Resources Information Center

Lewkow, Nicholas; Zimmerman, Neil; Riedesel, Mark; Essa, Alfred

2015-01-01

Next generation digital learning environments require delivering "just-in-time feedback" to learners and those who support them. Unlike traditional business intelligence environments, streaming data requires resilient infrastructure that can move data at scale from heterogeneous data sources, process the data quickly for use across…

A Framework System for Intelligent Support in Open Distributed Learning Environments--A Look Back from 16 Years Later

ERIC Educational Resources Information Center

Hoppe, H. Ulrich

2016-01-01

The 1998 paper by Martin Mühlenbrock, Frank Tewissen, and myself introduced a multi-agent architecture and a component engineering approach for building open distributed learning environments to support group learning in different types of classroom settings. It took up prior work on "multiple student modeling" as a method to configure…

Emotional Intelligence as a Determinant of Readiness for Online Learning

ERIC Educational Resources Information Center

Buzdar, Muhammad Ayub; Ali, Akhtar; Tariq, Riaz Ul Haq

2016-01-01

Students' performance in online learning environments is associated with their readiness to adopt a digital learning approach. Traditional concept of readiness for online learning is connected with students' competencies of using technology for learning purposes. We in this research, however, investigated psychometric aspects of students'…

A Survey on Ambient Intelligence in Health Care

PubMed Central

Acampora, Giovanni; Cook, Diane J.; Rashidi, Parisa; Vasilakos, Athanasios V.

2013-01-01

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people’s capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users’ goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths. PMID:24431472

A Survey on Ambient Intelligence in Health Care.

PubMed

Acampora, Giovanni; Cook, Diane J; Rashidi, Parisa; Vasilakos, Athanasios V

2013-12-01

Ambient Intelligence (AmI) is a new paradigm in information technology aimed at empowering people's capabilities by the means of digital environments that are sensitive, adaptive, and responsive to human needs, habits, gestures, and emotions. This futuristic vision of daily environment will enable innovative human-machine interactions characterized by pervasive, unobtrusive and anticipatory communications. Such innovative interaction paradigms make ambient intelligence technology a suitable candidate for developing various real life solutions, including in the health care domain. This survey will discuss the emergence of ambient intelligence (AmI) techniques in the health care domain, in order to provide the research community with the necessary background. We will examine the infrastructure and technology required for achieving the vision of ambient intelligence, such as smart environments and wearable medical devices. We will summarize of the state of the art artificial intelligence methodologies used for developing AmI system in the health care domain, including various learning techniques (for learning from user interaction), reasoning techniques (for reasoning about users' goals and intensions) and planning techniques (for planning activities and interactions). We will also discuss how AmI technology might support people affected by various physical or mental disabilities or chronic disease. Finally, we will point to some of the successful case studies in the area and we will look at the current and future challenges to draw upon the possible future research paths.

Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

NASA Astrophysics Data System (ADS)

Noor, Ahmed K.

2013-12-01

Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of the vision, intelligent adaptive cyber-physical ecosystems need to be developed to facilitate collaboration between the various stakeholders of engineering education, and to accelerate the development of a skilled engineering workforce. The major components of the ecosystems include integrated knowledge discovery and exploitation facilities, blended learning and research spaces, novel ultra-intelligent software agents, multimodal and autonomous interfaces, and networked cognitive and tele-presence robots.

Intelligence.

PubMed

Sternberg, Robert J

2012-03-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

Intelligence

PubMed Central

Sternberg, Robert J.

2012-01-01

Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

A Flowchart-Based Intelligent Tutoring System for Improving Problem-Solving Skills of Novice Programmers

ERIC Educational Resources Information Center

Hooshyar, D.; Ahmad, R. B.; Yousefi, M.; Yusop, F. D.; Horng, S.-J.

2015-01-01

Intelligent tutoring and personalization are considered as the two most important factors in the research of learning systems and environments. An effective tool that can be used to improve problem-solving ability is an Intelligent Tutoring System which is capable of mimicking a human tutor's actions in implementing a one-to-one personalized and…

Present situation and trend of precision guidance technology and its intelligence

NASA Astrophysics Data System (ADS)

Shang, Zhengguo; Liu, Tiandong

2017-11-01

This paper first introduces the basic concepts of precision guidance technology and artificial intelligence technology. Then gives a brief introduction of intelligent precision guidance technology, and with the help of development of intelligent weapon based on deep learning project in foreign: LRASM missile project, TRACE project, and BLADE project, this paper gives an overview of the current foreign precision guidance technology. Finally, the future development trend of intelligent precision guidance technology is summarized, mainly concentrated in the multi objectives, intelligent classification, weak target detection and recognition, intelligent between complex environment intelligent jamming and multi-source, multi missile cooperative fighting and other aspects.

Do individual differences in children's curiosity relate to their inquiry-based learning?

NASA Astrophysics Data System (ADS)

van Schijndel, Tessa J. P.; Jansen, Brenda R. J.; Raijmakers, Maartje E. J.

2018-06-01

This study investigates how individual differences in 7- to 9-year-olds' curiosity relate to the inquiry-learning process and outcomes in environments differing in structure. The focus on curiosity as individual differences variable was motivated by the importance of curiosity in science education, and uncertainty being central to both the definition of curiosity and the inquiry-learning environment. Curiosity was assessed with the Underwater Exploration game (Jirout, J., & Klahr, D. (2012). Children's scientific curiosity: In search of an operational definition of an elusive concept. Developmental Review, 32, 125-160. doi:10.1016/j.dr.2012.04.002), and inquiry-based learning with the newly developed Scientific Discovery task, which focuses on the principle of designing informative experiments. Structure of the inquiry-learning environment was manipulated by explaining this principle or not. As intelligence relates to learning and possibly curiosity, it was taken into account. Results showed that children's curiosity was positively related to their knowledge acquisition, but not to their quality of exploration. For low intelligent children, environment structure positively affected their quality of exploration, but not their knowledge acquisition. There was no interaction between curiosity and environment structure. These results support the existence of two distinct inquiry-based learning processes - the designing of experiments, on the one hand, and the reflection on performed experiments, on the other - and link children's curiosity to the latter process.

Collaborative Learning and Knowledge-Construction through a Knowledge-Based WWW Authoring Tool.

ERIC Educational Resources Information Center

Haugsjaa, Erik

This paper outlines hurdles to using the World Wide Web for learning, specifically in a collaborative knowledge-construction environment. Theoretical solutions based directly on existing Web environments, as well as on research and system prototypes in the areas of Intelligent Tutoring Systems (ITS) and ITS authoring systems, are suggested. Topics…

A Hybrid Approach for Supporting Adaptivity in E-Learning Environments

ERIC Educational Resources Information Center

Al-Omari, Mohammad; Carter, Jenny; Chiclana, Francisco

2016-01-01

Purpose: The purpose of this paper is to identify a framework to support adaptivity in e-learning environments. The framework reflects a novel hybrid approach incorporating the concept of the event-condition-action (ECA) model and intelligent agents. Moreover, a system prototype is developed reflecting the hybrid approach to supporting adaptivity…

PlayPhysics: An Emotional Games Learning Environment for Teaching Physics

NASA Astrophysics Data System (ADS)

Muñoz, Karla; Kevitt, Paul Mc; Lunney, Tom; Noguez, Julieta; Neri, Luis

To ensure learning, game-based learning environments must incorporate assessment mechanisms, e.g. Intelligent Tutoring Systems (ITSs). ITSs are focused on recognising and influencing the learner's emotional or motivational states. This research focuses on designing and implementing an affective student model for intelligent gaming, which reasons about the learner's emotional state from cognitive and motivational variables using observable behaviour. A Probabilistic Relational Models (PRMs) approach is employed to derive Dynamic Bayesian Networks (DBNs). The model uses the Control-Value theory of 'achievement emotions' as a basis. A preliminary test was conducted to recognise the students' prospective-outcome emotions with results presented and discussed. PlayPhysics is an emotional games learning environment for teaching Physics. Once the affective student model proves effective it will be incorporated into PlayPhysics' architecture. The design, evaluation and postevaluation of PlayPhysics are also discussed. Future work will focus on evaluating the affective student model with a larger population of students, and on providing affective feedback.

Fundamentals of the Design and the Operation of an Intelligent Tutoring System for the Learning of the Arithmetical and Algebraic Way of Solving Word Problems

ERIC Educational Resources Information Center

Arnau, David; Arevalillo-Herraez, Miguel; Puig, Luis; Gonzalez-Calero, Jose Antonio

2013-01-01

Designers of interactive learning environments with a focus on word problem solving usually have to compromise between the amount of resolution paths that a user is allowed to follow and the quality of the feedback provided. We have built an intelligent tutoring system (ITS) that is able to both track the user's actions and provide adequate…

Applying Adaptive Swarm Intelligence Technology with Structuration in Web-Based Collaborative Learning

ERIC Educational Resources Information Center

Huang, Yueh-Min; Liu, Chien-Hung

2009-01-01

One of the key challenges in the promotion of web-based learning is the development of effective collaborative learning environments. We posit that the structuration process strongly influences the effectiveness of technology used in web-based collaborative learning activities. In this paper, we propose an ant swarm collaborative learning (ASCL)…

Collaboration and Computer-Assisted Acquisition of a Second Language.

ERIC Educational Resources Information Center

Renie, Delphine; Chanier, Thierry

1995-01-01

Discusses how collaborative learning (CL) can be used in a computer-assisted learning (CAL) environment for language learning, reviewing research in the fields of applied linguistics, educational psychology, and artificial intelligence. An application of CL and CAL in the learning of French as a Second Language, focusing on interrogative…

Conceptual Learning with Multiple Graphical Representations: Intelligent Tutoring Systems Support for Sense-Making and Fluency-Building Processes

ERIC Educational Resources Information Center

Rau, Martina A.

2013-01-01

Most learning environments in the STEM disciplines use multiple graphical representations along with textual descriptions and symbolic representations. Multiple graphical representations are powerful learning tools because they can emphasize complementary aspects of complex learning contents. However, to benefit from multiple graphical…

A Hypermedia Approach to the Design of an Intelligent Tutoring System

DTIC Science & Technology

1991-09-01

23 3. Artist and Exploration Method ........................................... 24 4. Research method...LIMITATIONS AND FUTURE RESEARCH ............................................................... 76 v B. A CASE FOR HYPERMEDIA LEARNING ENVIRONMENTS...119 vi I. INTRODUCTION Most of the prior research in the field of intelligent tutoring systems (ITS) has focused on

Individualized Special Education with Cognitive Skill Assessment.

ERIC Educational Resources Information Center

Kurhila, Jaakko; Laine, Tei

2000-01-01

Describes AHMED (Adaptive and Assistive Hypermedia in Education), a computer learning environment which supports the evaluation of disabled children's cognitive skills in addition to supporting openness in learning materials and adaptivity in learning events. Discusses cognitive modeling and compares it to previous intelligent tutoring systems.…

Design and Control of Large Collections of Learning Agents

NASA Technical Reports Server (NTRS)

Agogino, Adrian

2001-01-01

The intelligent control of multiple autonomous agents is an important yet difficult task. Previous methods used to address this problem have proved to be either too brittle, too hard to use, or not scalable to large systems. The 'Collective Intelligence' project at NASA/Ames provides an elegant, machine-learning approach to address these problems. This approach mathematically defines some essential properties that a reward system should have to promote coordinated behavior among reinforcement learners. This work has focused on creating additional key properties and algorithms within the mathematics of the Collective Intelligence framework. One of the additions will allow agents to learn more quickly, in a more coordinated manner. The other will let agents learn with less knowledge of their environment. These additions will allow the framework to be applied more easily, to a much larger domain of multi-agent problems.

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

NASA Technical Reports Server (NTRS)

Lin, Paul P.; Jules, Kenol

2002-01-01

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen's self-organizing feature map, learning vector quantization, and back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.

Deductive Error Diagnosis and Inductive Error Generalization for Intelligent Tutoring Systems.

ERIC Educational Resources Information Center

Hoppe, H. Ulrich

1994-01-01

Examines the deductive approach to error diagnosis for intelligent tutoring systems. Topics covered include the principles of the deductive approach to diagnosis; domain-specific heuristics to solve the problem of generalizing error patterns; and deductive diagnosis and the hypertext-based learning environment. (Contains 26 references.) (JLB)

Design of Teacher Assistance Tools in an Exploratory Learning Environment for Algebraic Generalization

ERIC Educational Resources Information Center

Gutierrez-Santos, S.; Geraniou, E.; Pearce-Lazard, D.; Poulovassilis, A.

2012-01-01

The MiGen project is designing and developing an intelligent exploratory environment to support 11-14-year-old students in their learning of algebraic generalization. Deployed within the classroom, the system also provides tools to assist teachers in monitoring students' activities and progress. This paper describes the design of these Teacher…

Intelligent Assistance for Teachers in Collaborative E-Learning Environments

ERIC Educational Resources Information Center

Casamayor, Agustin; Amandi, Analia; Campo, Marcelo

2009-01-01

Collaborative learning environments provide a set of tools for students acting in groups to interact and accomplish an assigned task. In this kind of systems, students are free to express and communicate with each other, which usually lead to collaboration and communication problems that may require the intervention of a teacher. In this article,…

Progressions of Qualitative Models as a Foundation for Intelligent Learning Environments. Report No. 6277.

ERIC Educational Resources Information Center

White, Barbara Y.; Frederiksen, John R.

This report discusses the importance of presenting qualitative, causally consistent models in the initial stages of learning so that students can gain an understanding of basic electrical circuit concepts and principles that builds on their preexisting ways of reasoning about physical phenomena, and it argues that tutoring environments must help…

Linking Emotional Intelligence to Achieve Technology Enhanced Learning in Higher Education

ERIC Educational Resources Information Center

Kruger, Janette; Blignaut, A. Seugnet

2013-01-01

Higher education institutions (HEIs) increasingly use technology-enhanced learning (TEL) environments (e.g. blended learning and e-learning) to improve student throughput and retention rates. As the demand for TEL courses increases, expectations rise for faculty to meet the challenge of using TEL effectively. The promises that TEL holds have not…

An Intelligent Mobile Location-Aware Book Recommendation System that Enhances Problem-Based Learning in Libraries

ERIC Educational Resources Information Center

Chen, Chih-Ming

2013-01-01

Despite rapid and continued adoption of mobile devices, few learning modes integrate with mobile technologies and libraries' environments as innovative learning modes that emphasize the key roles of libraries in facilitating learning. In addition, some education experts have claimed that transmitting knowledge to learners is not the only…

Go outside to Learn: The Value of Outdoor Learning Environments

ERIC Educational Resources Information Center

Randall, Robin R.

2012-01-01

Outdoors opens up endless possibilities. Every place and space people experience offers an opportunity to learn. Accepted educational research first theorized by social scientist and author, Howard Gardner, shows that learners have nine multiple intelligences--visual, logical, intrapersonal, musical, body-kinesthetic, linguistic, interpersonal,…

Associative memory for online learning in noisy environments using self-organizing incremental neural network.

PubMed

Sudo, Akihito; Sato, Akihiro; Hasegawa, Osamu

2009-06-01

Associative memory operating in a real environment must perform well in online incremental learning and be robust to noisy data because noisy associative patterns are presented sequentially in a real environment. We propose a novel associative memory that satisfies these requirements. Using the proposed method, new associative pairs that are presented sequentially can be learned accurately without forgetting previously learned patterns. The memory size of the proposed method increases adaptively with learning patterns. Therefore, it suffers neither redundancy nor insufficiency of memory size, even in an environment in which the maximum number of associative pairs to be presented is unknown before learning. Noisy inputs in real environments are classifiable into two types: noise-added original patterns and faultily presented random patterns. The proposed method deals with two types of noise. To our knowledge, no conventional associative memory addresses noise of both types. The proposed associative memory performs as a bidirectional one-to-many or many-to-one associative memory and deals not only with bipolar data, but also with real-valued data. Results demonstrate that the proposed method's features are important for application to an intelligent robot operating in a real environment. The originality of our work consists of two points: employing a growing self-organizing network for an associative memory, and discussing what features are necessary for an associative memory for an intelligent robot and proposing an associative memory that satisfies those requirements.

Designing Writing Exercises to Emphasize Environmental Education

NASA Astrophysics Data System (ADS)

Narayanan, M.

2008-12-01

In this presentation, the author stresses the importance of writing exercises to educate students in certain disciplines. The objective is to make the students become personally involved so that their educational experience is more geared towards a learning paradigm instead of a teaching paradigm. In addition to accumulating a wealth of knowledge the students also refine and expand their writing skills and abilities. One should be pragmatic in one's approach. In other words, the instructor should have a clear understanding of the skills the students need to develop. It is important to define the target and implementation mode while designing writing exercises. Effective learning can thus be combined with enthusiasm in classroom instructional development. It is extremely important that all undergraduate engineering students are provided with an adequate understanding and thorough background of the National Environmental Policy Act (NEPA) of 1969. At present, undergraduate students at Miami University of Ohio do not acquire any knowledge pertaining to this particular topic. The author proposes that a topic based on NEPA be introduced in the Fluid Mechanics Course at a Junior Level. The author believes that there is an absolute and urgent need for introducing the students to the fact that various documents such as EA (Environmental Assessment), EIS (Environmental Impact Statement), FONSI (Finding Of No Significant Impact), are an essential part of present-day workplace environment. In this presentation the author talks about introducing NEPA in the classroom. More than a decade ago Harvard University Professor Dr. Howard Gardner suggested the theory of Multiple Intelligences. Dr. Gardner proposed that eight different Intelligences accounted for the development of human potential (Gardner, 1983, 1993, 2000). Leading scholars in the area of Cognitive Science and Educational Methodologies also agree and have concluded that it is essential that students need to be taught in a learning environment that enables them to acquire real-world problem-solving skills (Saxe, 1988; Senge, 1990; Sims, 1995). Educators should not allow the students to wonder whether they have been learning anything that would actually serve them in the workplace, upon graduation. (Barr and Tagg, 1995). Howard Gardner's list of Eight Intelligences is given below. 1. Linguistic intelligence ("word smart") 2. Logical intelligence ("number smart") 3. Spatial intelligence ("picture smart") 4. Kinesthetic intelligence ("body smart") 5. Musical intelligence ("music smart") 6. Interpersonal intelligence ("people smart") 7. Intrapersonal intelligence ("self smart") 8. Naturalist intelligence ("nature smart") The author has tried to examine students' learning development, behavior and exploration using some of the above eight Intelligences. In this presentation, he provides data he has collected while teaching certain selected courses (Narayanan, 2007). References Gardner, Howard. Frames of Mind: The Theory of Multiple Intelligences. New York: Basic,1983 Gardner, Howard. Multiple Intelligences: The Theory in Practice. New York: Basic, 1993. Gardner, Howard. Intelligence Reframed: Multiple Intelligences for the 21st Century. New York: Basic, 2000. Barr, R. B., and Tagg, J. (1995, November/December). From teaching to learning: A new paradigm for undergraduate education. Change: The Magazine of Higher Education, 13-24. Narayanan, Mysore (2007). Assessment of Perceptual Modality Styles. Proceedings of ASEE 2007 Annual Conference, Honolulu, Hawaii.

A Proposed Intelligent Policy-Based Interface for a Mobile eHealth Environment

NASA Astrophysics Data System (ADS)

Tavasoli, Amir; Archer, Norm

Users of mobile eHealth systems are often novices, and the learning process for them may be very time consuming. In order for systems to be attractive to potential adopters, it is important that the interface should be very convenient and easy to learn. However, the community of potential users of a mobile eHealth system may be quite varied in their requirements, so the system must be able to adapt easily to suit user preferences. One way to accomplish this is to have the interface driven by intelligent policies. These policies can be refined gradually, using inputs from potential users, through intelligent agents. This paper develops a framework for policy refinement for eHealth mobile interfaces, based on dynamic learning from user interactions.

Sensory grammars for sensor networks

PubMed Central

Aloimonos, Yiannis

2009-01-01

One of the major goals of Ambient Intelligence and Smart Environments is to interpret human activity sensed by a variety of sensors. In order to develop useful technologies and a subsequent industry around smart environments, we need to proceed in a principled manner. This paper suggests that human activity can be expressed in a language. This is a special language with its own phonemes, its own morphemes (words) and its own syntax and it can be learned using machine learning techniques applied to gargantuan amounts of data collected by sensor networks. Developing such languages will create bridges between Ambient Intelligence and other disciplines. It will also provide a hierarchical structure that can lead to a successful industry. PMID:21897837

An Ontology for Learning Services on the Shop Floor

ERIC Educational Resources Information Center

Ullrich, Carsten

2016-01-01

An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as…

Experimental Evaluation of Performance Feedback Using the Dismounted Infantry Virtual After Action Review System. Long Range Navy and Marine Corps Science and Technology Program

DTIC Science & Technology

2007-11-14

Artificial intelligence and 4 23 education , Volume 1: Learning environments and tutoring systems. Hillsdale, NJ: Erlbaum. Wickens, C.D. (1984). Processing...and how to use it to best optimize the learning process. Some researchers (see Loftin & Savely, 1991) have proposed adding intelligent systems to the...is experienced as the cognitive centers in an individual’s brain process visual, tactile, kinesthetic , olfactory, proprioceptive, and auditory

Design of cognitive engine for cognitive radio based on the rough sets and radial basis function neural network

NASA Astrophysics Data System (ADS)

Yang, Yanchao; Jiang, Hong; Liu, Congbin; Lan, Zhongli

2013-03-01

Cognitive radio (CR) is an intelligent wireless communication system which can dynamically adjust the parameters to improve system performance depending on the environmental change and quality of service. The core technology for CR is the design of cognitive engine, which introduces reasoning and learning methods in the field of artificial intelligence, to achieve the perception, adaptation and learning capability. Considering the dynamical wireless environment and demands, this paper proposes a design of cognitive engine based on the rough sets (RS) and radial basis function neural network (RBF_NN). The method uses experienced knowledge and environment information processed by RS module to train the RBF_NN, and then the learning model is used to reconfigure communication parameters to allocate resources rationally and improve system performance. After training learning model, the performance is evaluated according to two benchmark functions. The simulation results demonstrate the effectiveness of the model and the proposed cognitive engine can effectively achieve the goal of learning and reconfiguration in cognitive radio.

Does Learning to Read Improve Intelligence? A Longitudinal Multivariate Analysis in Identical Twins From Age 7 to 16

PubMed Central

Ritchie, Stuart J; Bates, Timothy C; Plomin, Robert

2015-01-01

Evidence from twin studies points to substantial environmental influences on intelligence, but the specifics of this influence are unclear. This study examined one developmental process that potentially causes intelligence differences: learning to read. In 1,890 twin pairs tested at 7, 9, 10, 12, and 16 years, a cross-lagged monozygotic-differences design was used to test for associations of earlier within-pair reading ability differences with subsequent intelligence differences. The results showed several such associations, which were not explained by differences in reading exposure and were not restricted to verbal cognitive domains. The study highlights the potentially important influence of reading ability, driven by the nonshared environment, on intellectual development and raises theoretical questions about the mechanism of this influence. PMID:25056688

An E-learning System based on Affective Computing

NASA Astrophysics Data System (ADS)

Duo, Sun; Song, Lu Xue

In recent years, e-learning as a learning system is very popular. But the current e-learning systems cannot instruct students effectively since they do not consider the emotional state in the context of instruction. The emergence of the theory about "Affective computing" can solve this question. It can make the computer's intelligence no longer be a pure cognitive one. In this paper, we construct an emotional intelligent e-learning system based on "Affective computing". A dimensional model is put forward to recognize and analyze the student's emotion state and a virtual teacher's avatar is offered to regulate student's learning psychology with consideration of teaching style based on his personality trait. A "man-to-man" learning environment is built to simulate the traditional classroom's pedagogy in the system.

Transformed Telepresence and Its Association with Learning in Computer-Supported Collaborative Learning: A Case Study in English Learning and Its Evaluation

ERIC Educational Resources Information Center

Ting, Yu-Liang; Tai, Yaming; Chen, Jun-Horng

2017-01-01

Telepresence has been playing an important role in a mediated learning environment. However, the current design of telepresence seems to be dominated by the emulation of physical human presence. With reference to social constructivism learning and the recognition of individuals as intelligent entities, this study explored the transformation of…

Intelligent computer-aided training authoring environment

NASA Technical Reports Server (NTRS)

Way, Robert D.

1994-01-01

Although there has been much research into intelligent tutoring systems (ITS), there are few authoring systems available that support ITS metaphors. Instructional developers are generally obliged to use tools designed for creating on-line books. We are currently developing an authoring environment derived from NASA's research on intelligent computer-aided training (ICAT). The ICAT metaphor, currently in use at NASA has proven effective in disciplines from satellite deployment to high school physics. This technique provides a personal trainer (PT) who instructs the student using a simulated work environment (SWE). The PT acts as a tutor, providing individualized instruction and assistance to each student. Teaching in an SWE allows the student to learn tasks by doing them, rather than by reading about them. This authoring environment will expedite ICAT development by providing a tool set that guides the trainer modeling process. Additionally, this environment provides a vehicle for distributing NASA's ICAT technology to the private sector.

The "Total Immersion" Meeting Environment.

ERIC Educational Resources Information Center

Finkel, Coleman

1980-01-01

The designing of intelligently planned meeting facilities can aid management communication and learning. The author examines the psychology of meeting attendance; architectural considerations (lighting, windows, color, etc.); design elements and learning modes (furniture, walls, audiovisuals, materials); and the idea of "total immersion meeting…

A deep convolutional neural network with new training methods for bearing fault diagnosis under noisy environment and different working load

NASA Astrophysics Data System (ADS)

Zhang, Wei; Li, Chuanhao; Peng, Gaoliang; Chen, Yuanhang; Zhang, Zhujun

2018-02-01

In recent years, intelligent fault diagnosis algorithms using machine learning technique have achieved much success. However, due to the fact that in real world industrial applications, the working load is changing all the time and noise from the working environment is inevitable, degradation of the performance of intelligent fault diagnosis methods is very serious. In this paper, a new model based on deep learning is proposed to address the problem. Our contributions of include: First, we proposed an end-to-end method that takes raw temporal signals as inputs and thus doesn't need any time consuming denoising preprocessing. The model can achieve pretty high accuracy under noisy environment. Second, the model does not rely on any domain adaptation algorithm or require information of the target domain. It can achieve high accuracy when working load is changed. To understand the proposed model, we will visualize the learned features, and try to analyze the reasons behind the high performance of the model.

Brief Report: Evaluation of an Intelligent Learning Environment for Young Children with Autism Spectrum Disorder.

PubMed

Zheng, Zhi; Warren, Zachary; Weitlauf, Amy; Fu, Qiang; Zhao, Huan; Swanson, Amy; Sarkar, Nilanjan

2016-11-01

Researchers are increasingly attempting to develop and apply innovative technological platforms for early detection and intervention of autism spectrum disorder (ASD). This pilot study designed and evaluated a novel technologically-mediated intelligent learning environment with relevance to early social orienting skills. The environment was endowed with the capacity to administer social orienting cues and adaptively respond to autonomous real-time measurement of performance (i.e., non-contact gaze measurement). We evaluated the system with both toddlers with ASD (n = 8) as well as typically developing infants (n = 8). Children in both groups were able to ultimately respond accurately to social prompts delivered by the technological system. Results also indicated that the system was capable of attracting and pushing toward correct performance autonomously without user intervention.

Smart-system of distance learning of visually impaired people based on approaches of artificial intelligence

NASA Astrophysics Data System (ADS)

Samigulina, Galina A.; Shayakhmetova, Assem S.

2016-11-01

Research objective is the creation of intellectual innovative technology and information Smart-system of distance learning for visually impaired people. The organization of the available environment for receiving quality education for visually impaired people, their social adaptation in society are important and topical issues of modern education.The proposed Smart-system of distance learning for visually impaired people can significantly improve the efficiency and quality of education of this category of people. The scientific novelty of proposed Smart-system is using intelligent and statistical methods of processing multi-dimensional data, and taking into account psycho-physiological characteristics of perception and awareness learning information by visually impaired people.

Bio-robots automatic navigation with graded electric reward stimulation based on Reinforcement Learning.

PubMed

Zhang, Chen; Sun, Chao; Gao, Liqiang; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2013-01-01

Bio-robots based on brain computer interface (BCI) suffer from the lack of considering the characteristic of the animals in navigation. This paper proposed a new method for bio-robots' automatic navigation combining the reward generating algorithm base on Reinforcement Learning (RL) with the learning intelligence of animals together. Given the graded electrical reward, the animal e.g. the rat, intends to seek the maximum reward while exploring an unknown environment. Since the rat has excellent spatial recognition, the rat-robot and the RL algorithm can convergent to an optimal route by co-learning. This work has significant inspiration for the practical development of bio-robots' navigation with hybrid intelligence.

Architectures for Distributed and Complex M-Learning Systems: Applying Intelligent Technologies

ERIC Educational Resources Information Center

Caballe, Santi, Ed.; Xhafa, Fatos, Ed.; Daradoumis, Thanasis, Ed.; Juan, Angel A., Ed.

2009-01-01

Over the last decade, the needs of educational organizations have been changing in accordance with increasingly complex pedagogical models and with the technological evolution of e-learning environments with very dynamic teaching and learning requirements. This book explores state-of-the-art software architectures and platforms used to support…

Intelligent Agents for Dynamic Optimization of Learner Performances in an Online System

ERIC Educational Resources Information Center

Kamsa, Imane; Elouahbi, Rachid; El Khoukhi, Fatima

2017-01-01

Aim/Purpose: To identify and rectify the learning difficulties of online learners. Background: The major cause of learners' failure and non-acquisition of knowledge relates to their weaknesses in certain areas necessary for optimal learning. We focus on e-learning because, within this environment, the learner is mostly affected by these…

Representing System Behaviors and Expert Behaviors for Intelligent Tutoring

DTIC Science & Technology

1987-02-09

Learned .................................. 44 . Future Directions ................................... 47 Sum m ary...and training environments to assist the instructor in meeting the students’ learning needs. The first application of the IMTS will be in training...identifies and resolves learning deficiencies and minimizes unproductive practice time. Another decision made early in the planning phase was to place

Effects of Group Reflection Variations in Project-Based Learning Integrated in a Web 2.0 Learning Space

ERIC Educational Resources Information Center

Kim, Paul; Hong, Ji-Seong; Bonk, Curtis; Lim, Gloria

2011-01-01

A Web 2.0 environment that is coupled with emerging multimodal interaction tools can have considerable influence on team learning outcomes. Today, technologies supporting social networking, collective intelligence, emotional interaction, and virtual communication are introducing new forms of collaboration that are profoundly impacting education.…

Interaction Network Estimation: Predicting Problem-Solving Diversity in Interactive Environments

ERIC Educational Resources Information Center

Eagle, Michael; Hicks, Drew; Barnes, Tiffany

2015-01-01

Intelligent tutoring systems and computer aided learning environments aimed at developing problem solving produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled student-tutor interactions using complex networks in…

A cognitive robotic system based on the Soar cognitive architecture for mobile robot navigation, search, and mapping missions

NASA Astrophysics Data System (ADS)

Hanford, Scott D.

Most unmanned vehicles used for civilian and military applications are remotely operated or are designed for specific applications. As these vehicles are used to perform more difficult missions or a larger number of missions in remote environments, there will be a great need for these vehicles to behave intelligently and autonomously. Cognitive architectures, computer programs that define mechanisms that are important for modeling and generating domain-independent intelligent behavior, have the potential for generating intelligent and autonomous behavior in unmanned vehicles. The research described in this presentation explored the use of the Soar cognitive architecture for cognitive robotics. The Cognitive Robotic System (CRS) has been developed to integrate software systems for motor control and sensor processing with Soar for unmanned vehicle control. The CRS has been tested using two mobile robot missions: outdoor navigation and search in an indoor environment. The use of the CRS for the outdoor navigation mission demonstrated that a Soar agent could autonomously navigate to a specified location while avoiding obstacles, including cul-de-sacs, with only a minimal amount of knowledge about the environment. While most systems use information from maps or long-range perceptual capabilities to avoid cul-de-sacs, a Soar agent in the CRS was able to recognize when a simple approach to avoiding obstacles was unsuccessful and switch to a different strategy for avoiding complex obstacles. During the indoor search mission, the CRS autonomously and intelligently searches a building for an object of interest and common intersection types. While searching the building, the Soar agent builds a topological map of the environment using information about the intersections the CRS detects. The agent uses this topological model (along with Soar's reasoning, planning, and learning mechanisms) to make intelligent decisions about how to effectively search the building. Once the object of interest has been detected, the Soar agent uses the topological map to make decisions about how to efficiently return to the location where the mission began. Additionally, the CRS can send an email containing step-by-step directions using the intersections in the environment as landmarks that describe a direct path from the mission's start location to the object of interest. The CRS has displayed several characteristics of intelligent behavior, including reasoning, planning, learning, and communication of learned knowledge, while autonomously performing two missions. The CRS has also demonstrated how Soar can be integrated with common robotic motor and perceptual systems that complement the strengths of Soar for unmanned vehicles and is one of the few systems that use perceptual systems such as occupancy grid, computer vision, and fuzzy logic algorithms with cognitive architectures for robotics. The use of these perceptual systems to generate symbolic information about the environment during the indoor search mission allowed the CRS to use Soar's planning and learning mechanisms, which have rarely been used by agents to control mobile robots in real environments. Additionally, the system developed for the indoor search mission represents the first known use of a topological map with a cognitive architecture on a mobile robot. The ability to learn both a topological map and production rules allowed the Soar agent used during the indoor search mission to make intelligent decisions and behave more efficiently as it learned about its environment. While the CRS has been applied to two different missions, it has been developed with the intention that it be extended in the future so it can be used as a general system for mobile robot control. The CRS can be expanded through the addition of new sensors and sensor processing algorithms, development of Soar agents with more production rules, and the use of new architectural mechanisms in Soar.

Linking Immersive Virtual Field Trips with an Adaptive Learning Platform

NASA Astrophysics Data System (ADS)

Bruce, G.; Taylor, W.; Anbar, A. D.; Semken, S. C.; Buxner, S.; Mead, C.; El-Moujaber, E.; Summons, R. E.; Oliver, C.

2016-12-01

The use of virtual environments in science education has been constrained by the difficulty of guiding a learner's actions within the those environments. In this work, we demonstrate how advances in education software technology allow educators to create interactive learning experiences that respond and adapt intelligently to learner input within the virtual environment. This innovative technology provides a far greater capacity for delivering authentic inquiry-driven educational experiences in unique settings from around the world. Our immersive virtual field trips (iVFT) bring students virtually to geologically significant but inaccessible environments, where they learn through authentic practices of scientific inquiry. In one recent example, students explore the fossil beds in Nilpena, South Australia to learn about the Ediacaran fauna. Students interactively engage in 360° recreations of the environment, uncover the nature of the historical ecosystem by identifying fossils with a dichotomous key, explore actual fossil beds in high resolution imagery, and reconstruct what an ecosystem might have looked like millions of years ago in an interactive simulation. With the new capacity to connect actions within the iVFT to an intelligent tutoring system, these learning experiences can be tracked, guided, and tailored individually to the immediate actions of the student. This new capacity also has great potential for learning designers to take a data-driven approach to lesson improvement and for education researchers to study learning in virtual environments. Thus, we expect iVFT will be fertile ground for novel research. Such iVFT are currently in use in several introductory classes offered online at Arizona State University in anthropology, introductory biology, and astrobiology, reaching thousands of students to date. Drawing from these experiences, we are designing a curriculum for historical geology that will be built around iVFT-based exploration of Earth history.

Work Integrated Learning Competencies: Industrial Supervisors' Perspectives

ERIC Educational Resources Information Center

Makhathini, Thobeka Pearl

2016-01-01

Research on student-learning outcomes indicates that university graduates do not possess relevant skills required by the industry such as leadership, emotional intelligence, problem solving, communication, decision-making skills and the ability to function in a multicultural environment. Currently, engineering graduates are expected to perform…

Deep imitation learning for 3D navigation tasks.

PubMed

Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina

2018-01-01

Deep learning techniques have shown success in learning from raw high-dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imitation learning has been scarcely explored. Imitation learning can be an efficient method to teach intelligent agents by providing a set of demonstrations to learn from. However, generalizing to situations that are not represented in the demonstrations can be challenging, especially in 3D environments. In this paper, we propose a deep imitation learning method to learn navigation tasks from demonstrations in a 3D environment. The supervised policy is refined using active learning in order to generalize to unseen situations. This approach is compared to two popular deep reinforcement learning techniques: deep-Q-networks and Asynchronous actor-critic (A3C). The proposed method as well as the reinforcement learning methods employ deep convolutional neural networks and learn directly from raw visual input. Methods for combining learning from demonstrations and experience are also investigated. This combination aims to join the generalization ability of learning by experience with the efficiency of learning by imitation. The proposed methods are evaluated on 4 navigation tasks in a 3D simulated environment. Navigation tasks are a typical problem that is relevant to many real applications. They pose the challenge of requiring demonstrations of long trajectories to reach the target and only providing delayed rewards (usually terminal) to the agent. The experiments show that the proposed method can successfully learn navigation tasks from raw visual input while learning from experience methods fail to learn an effective policy. Moreover, it is shown that active learning can significantly improve the performance of the initially learned policy using a small number of active samples.

Cognitive Tutoring based on Intelligent Decision Support in the PENTHA Instructional Design Model

NASA Astrophysics Data System (ADS)

dall'Acqua, Luisa

2010-06-01

The research finality of this paper is how to support Authors to develop rule driven—subject oriented, adaptable course content, meta-rules—representing the disciplinary epistemology, model of teaching, Learning Path structure, and assessment parameters—for intelligent Tutoring actions in a personalized, adaptive e-Learning environment. The focus is to instruct the student to be a decision manager for himself, able to recognize the elements of a problem, select the necessary information with the perspective of factual choices. In particular, our research intends to provide some fundamental guidelines for the definition of didactical rules and logical relations, that Authors should provide to a cognitive Tutoring system through the use of an Instructional Design method (PENTHA Model) which proposes an educational environment, able to: increase productivity and operability, create conditions for a cooperative dialogue, developing participatory research activities of knowledge, observations and discoveries, customizing the learning design in a complex and holistic vision of the learning / teaching processes.

Intelligence: Real or artificial?

PubMed Central

Schlinger, Henry D.

1992-01-01

Throughout the history of the artificial intelligence movement, researchers have strived to create computers that could simulate general human intelligence. This paper argues that workers in artificial intelligence have failed to achieve this goal because they adopted the wrong model of human behavior and intelligence, namely a cognitive essentialist model with origins in the traditional philosophies of natural intelligence. An analysis of the word “intelligence” suggests that it originally referred to behavior-environment relations and not to inferred internal structures and processes. It is concluded that if workers in artificial intelligence are to succeed in their general goal, then they must design machines that are adaptive, that is, that can learn. Thus, artificial intelligence researchers must discard their essentialist model of natural intelligence and adopt a selectionist model instead. Such a strategic change should lead them to the science of behavior analysis. PMID:22477051

A Comparison of Learning Environments: All That Glitters... Interim Technical Paper for Period January 1990-July 1991.

ERIC Educational Resources Information Center

Shute, Valerie J.

Aptitude-treatment interactions (ATIs) refer to the covariation between learner characteristic and instructional treatment in relation to some outcome measure. To systematically test for ATI, an intelligent tutoring system instructing in basic principles of electricity was chosen as a complex but controlled learning task. Two learning environments…

Intelligent flight control systems

NASA Technical Reports Server (NTRS)

Stengel, Robert F.

1993-01-01

The capabilities of flight control systems can be enhanced by designing them to emulate functions of natural intelligence. Intelligent control functions fall in three categories. Declarative actions involve decision-making, providing models for system monitoring, goal planning, and system/scenario identification. Procedural actions concern skilled behavior and have parallels in guidance, navigation, and adaptation. Reflexive actions are spontaneous, inner-loop responses for control and estimation. Intelligent flight control systems learn knowledge of the aircraft and its mission and adapt to changes in the flight environment. Cognitive models form an efficient basis for integrating 'outer-loop/inner-loop' control functions and for developing robust parallel-processing algorithms.

Serious Use of a Serious Game for Language Learning

ERIC Educational Resources Information Center

Johnson, W. Lewis

2010-01-01

The Tactical Language and Culture Training System (TLCTS) helps learners acquire basic communicative skills in foreign languages and cultures. Learners acquire communication skills through a combination of interactive lessons and serious games. Artificial intelligence plays multiple roles in this learning environment: to process the learner's…

Still Building Rafts, Juggling Balls and Driving Tanks?

ERIC Educational Resources Information Center

Beard, Colin; Wilson, John

2002-01-01

A model presents experiential learning as a combination lock. Outdoor environmental elements, activities, senses, emotions, forms of intelligence, and ways of learning are grouped into six "tumblers" that can be arranged into combinations that best help learners interact with the external environment through their senses, thus generating…

Cognitive Task Analysis and Intelligent Computer-Based Training Systems: Lessons Learned from Coached Practice Environments in Air Force Avionics.

ERIC Educational Resources Information Center

Katz, Sandra N.; Hall, Ellen; Lesgold, Alan

This paper describes some results of a collaborative effort between the University of Pittsburgh and the Air Force to develop advanced troubleshooting training for F-15 maintenance technicians. The focus is on the cognitive task methodology used in the development of three intelligent tutoring systems to inform their instructional content and…

Architecture for robot intelligence

NASA Technical Reports Server (NTRS)

Peters, II, Richard Alan (Inventor)

2004-01-01

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Mobile robots exploration through cnn-based reinforcement learning.

PubMed

Tai, Lei; Liu, Ming

2016-01-01

Exploration in an unknown environment is an elemental application for mobile robots. In this paper, we outlined a reinforcement learning method aiming for solving the exploration problem in a corridor environment. The learning model took the depth image from an RGB-D sensor as the only input. The feature representation of the depth image was extracted through a pre-trained convolutional-neural-networks model. Based on the recent success of deep Q-network on artificial intelligence, the robot controller achieved the exploration and obstacle avoidance abilities in several different simulated environments. It is the first time that the reinforcement learning is used to build an exploration strategy for mobile robots through raw sensor information.

Exploring Optimal Conditions of Instructional Guidance in an Algebra Tutor

ERIC Educational Resources Information Center

Lee, Hee Seung; Anderson, John R.; Berman, Susan R.; Ferris-Glick, Jennifer; Joshi, Ambarish; Nixon, Tristan; Ritter, Steve

2013-01-01

In designing learning environments that support student learning, there are many instructional design decisions. These include when and how to provide examples, verbal explanations, feedback, and other scaffolding features. In this paper, the authors investigate instructional guidance as it relates to Cognitive Tutor, an intelligent tutoring…

Whose Classroom Is It, Anyway? Improvisation as a Teaching Tool

ERIC Educational Resources Information Center

Berk, Ronald A.; Trieber, Rosalind H.

2009-01-01

Improvisational techniques derived from the experiences in improvisational theatre can be adapted for the college classroom to leverage the characteristics of the Net Generation, their multiple intelligences and learning styles, and the variety of collaborative learning activities already in place in a learner-centered environment. When…

An Intelligent Tutor for Basic Algebra.

ERIC Educational Resources Information Center

McArthur, David; Stasz, Cathleen

The stated goal of Individual Computer-Assisted Instruction (ICAI) research is the development of computer software that combines much of the subject matter being studied, any particular student's learning schema, and the pedagogical knowledge of human tutors into a powerful one-to-one learning environment. This report describes the initial steps…

The Impact of Emotional Arousal on Learning in Virtual Environments

DTIC Science & Technology

2002-09-01

intelligence (AI) algorithms, weapon fire/hit/miss rate, health of the players , etc.) within the actual code of the game/VE. No other game offered...experiment was conducted to observe learning differences in a low-arousal condition and a high-arousal condition. A first-person shooter videogame ...and a high-arousal condition. A first-person shooter videogame (America’s Army: Operations) was used as the virtual environment. In the low

An Intelligent Web-Based System for Diagnosing Student Learning Problems Using Concept Maps

ERIC Educational Resources Information Center

Acharya, Anal; Sinha, Devadatta

2017-01-01

The aim of this article is to propose a method for development of concept map in web-based environment for identifying concepts a student is deficient in after learning using traditional methods. Direct Hashing and Pruning algorithm was used to construct concept map. Redundancies within the concept map were removed to generate a learning sequence.…

Cultivating a Doctoral Community of Inquiry and Practice: Designing and Facilitating Discussion Board Online Learning Communities

ERIC Educational Resources Information Center

Hauser, Linda; Darrow, Rob

2013-01-01

This paper presents a promising and powerful approach used to cultivate a doctoral community of inquiry and practice and harness the intelligence, commitment, and energy of all of its members in a blended learning environment. The discussion board online learning community approach was developed to transform a traditional face-to-face doctoral…

Aspects of Plant Intelligence

PubMed Central

TREWAVAS, ANTHONY

2003-01-01

Intelligence is not a term commonly used when plants are discussed. However, I believe that this is an omission based not on a true assessment of the ability of plants to compute complex aspects of their environment, but solely a reflection of a sessile lifestyle. This article, which is admittedly controversial, attempts to raise many issues that surround this area. To commence use of the term intelligence with regard to plant behaviour will lead to a better understanding of the complexity of plant signal transduction and the discrimination and sensitivity with which plants construct images of their environment, and raises critical questions concerning how plants compute responses at the whole‐plant level. Approaches to investigating learning and memory in plants will also be considered. PMID:12740212

Increases in Emotional Intelligence After an Online Training Program Are Associated With Better Decision-Making on the Iowa Gambling Task.

PubMed

Alkozei, Anna; Smith, Ryan; Demers, Lauren A; Weber, Mareen; Berryhill, Sarah M; Killgore, William D S

2018-01-01

Higher levels of emotional intelligence have been associated with better inter and intrapersonal functioning. In the present study, 59 healthy men and women were randomized into either a three-week online training program targeted to improve emotional intelligence ( n = 29), or a placebo control training program targeted to improve awareness of nonemotional aspects of the environment ( n = 30). Compared to placebo, participants in the emotional intelligence training group showed increased performance on the total emotional intelligence score of the Mayer-Salovey-Caruso Emotional Intelligence Test, a performance measure of emotional intelligence, as well as subscales of perceiving emotions and facilitating thought. Moreover, after emotional intelligence training, but not after placebo training, individuals displayed the ability to arrive at optimal performance faster (i.e., they showed a faster learning rate) during an emotion-guided decision-making task (i.e., the Iowa Gambling Task). More specifically, although both groups showed similar performance at the start of the Iowa Gambling Task from pre- to posttraining, the participants in the emotional intelligence training group learned to choose more advantageous than disadvantageous decks than those in the placebo training group by the time they reached the "hunch" period of the task (i.e., the point in the task when implicit task learning is thought to have occurred). Greater total improvements in performance on the Iowa Gambling Task from pre- to posttraining in the emotional intelligence training group were also positively correlated with pre- to posttraining changes in Mayer-Salovey-Caruso Emotional Intelligence Test scores, in particular with changes in the ability to perceive emotions. The present study provides preliminary evidence that emotional intelligence can be trained with the help of an online training program targeted at adults; it also suggests that changes in emotional intelligence, as a result of such a program, can lead to improved emotion-guided decision-making.

DYNACLIPS (DYNAmic CLIPS): A dynamic knowledge exchange tool for intelligent agents

NASA Technical Reports Server (NTRS)

Cengeloglu, Yilmaz; Khajenoori, Soheil; Linton, Darrell

1994-01-01

In a dynamic environment, intelligent agents must be responsive to unanticipated conditions. When such conditions occur, an intelligent agent may have to stop a previously planned and scheduled course of actions and replan, reschedule, start new activities and initiate a new problem solving process to successfully respond to the new conditions. Problems occur when an intelligent agent does not have enough knowledge to properly respond to the new situation. DYNACLIPS is an implementation of a framework for dynamic knowledge exchange among intelligent agents. Each intelligent agent is a CLIPS shell and runs a separate process under SunOS operating system. Intelligent agents can exchange facts, rules, and CLIPS commands at run time. Knowledge exchange among intelligent agents at run times does not effect execution of either sender and receiver intelligent agent. Intelligent agents can keep the knowledge temporarily or permanently. In other words, knowledge exchange among intelligent agents would allow for a form of learning to be accomplished.

A Cybernetic Design Methodology for 'Intelligent' Online Learning Support

NASA Astrophysics Data System (ADS)

Quinton, Stephen R.

The World Wide Web (WWW) provides learners and knowledge workers convenient access to vast stores of information, so much that present methods for refinement of a query or search result are inadequate - there is far too much potentially useful material. The problem often encountered is that users usually do not recognise what may be useful until they have progressed some way through the discovery, learning, and knowledge acquisition process. Additional support is needed to structure and identify potentially relevant information, and to provide constructive feedback. In short, support for learning is needed. The learning envisioned here is not simply the capacity to recall facts or to recognise objects. The focus is on learning that results in the construction of knowledge. Although most online learning platforms are efficient at delivering information, most do not provide tools that support learning as envisaged in this chapter. It is conceivable that Web-based learning environments can incorporate software systems that assist learners to form new associations between concepts and synthesise information to create new knowledge. This chapter details the rationale and theory behind a research study that aims to evolve Web-based learning environments into 'intelligent thinking' systems that respond to natural language human input. Rather than functioning simply as a means of delivering information, it is argued that online learning solutions will 1 day interact directly with students to support their conceptual thinking and cognitive development.

Constructing a Deconstructed Campus: Instructional Design as Vital Bricks and Mortar

ERIC Educational Resources Information Center

Ross, Steven M.; Morrison, Gary R.

2012-01-01

In this rejoinder to Mazoue ("J Comput High Educ," 2012) article, "the deconstructed campus," we react to his arguments regarding the replacement of face-to-face teaching on college campuses with computer-supported approaches, including on-line learning, intelligent cognitive tutors, and open-ended learning environments where, rather than being…

Self-Regulatory Efficacy and Mindset of At-Risk Students: An Exploratory Study

ERIC Educational Resources Information Center

Matheson, Ian A.

2015-01-01

There is a limited body of research examining how students' beliefs about intelligence and about their abilities relate to different learning environments. As reported here, I examined secondary school students' beliefs, goals, and expectations guided by Zimmerman's (2000) model of self-regulated learning. In this exploratory study, 230 secondary…

Learning Motivation and Performance Excellence in Adolescents with High Intellectual Potential: What Really Matters?

ERIC Educational Resources Information Center

Schick, Hella; Phillipson, Shane N.

2009-01-01

In the development of performance excellence, the relative roles played by intellectual ability and motivation remain speculative. This study investigates the role played by general intelligence, school environment, self-efficacy, and aspects of personal identity in the formation of learning motivation in German students attending the Gymnasium…

Emotional Intelligence and Collaborative Learning in Adult Education

ERIC Educational Resources Information Center

Martinez, Luz M.

2011-01-01

The changing social and economic reality of our world continues to shape how learning is conducted and acquired in the adult classroom and beyond. Given the pivotal importance for an adult to develop a variety of cognitive and emotional skills and given the need to work in collaboration with others, within educational environments and the…

Subgroup Discovery with User Interaction Data: An Empirically Guided Approach to Improving Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Poitras, Eric G.; Lajoie, Susanne P.; Doleck, Tenzin; Jarrell, Amanda

2016-01-01

Learner modeling, a challenging and complex endeavor, is an important and oft-studied research theme in computer-supported education. From this perspective, Educational Data Mining (EDM) research has focused on modeling and comprehending various dimensions of learning in computer-based learning environments (CBLE). Researchers and designers are…

Motivation and Performance in a Game-Based Intelligent Tutoring System

ERIC Educational Resources Information Center

Jackson, G. Tanner; McNamara, Danielle S.

2013-01-01

One strength of educational games stems from their potential to increase students' motivation and engagement during educational tasks. However, game features may also detract from principle learning goals and interfere with students' ability to master the target material. To assess the potential impact of game-based learning environments, in this…

Learning Qualitative and Quantitative Reasoning in a Microworld for Elastic Impacts.

ERIC Educational Resources Information Center

Ploetzner, Rolf; And Others

1990-01-01

Discusses the artificial-intelligence-based microworld DiBi and MULEDS, a multilevel diagnosis system. Developed to adapt tutoring style to the individual learner. Explains that DiBi sets up a learning environment, and simulates elastic impacts as a subtopic of classical mechanics, and supporting reasoning on different levels of mental domain…

A Study of the Design and Implementation of the ASR-Based iCASL System with Corrective Feedback to Facilitate English Learning

ERIC Educational Resources Information Center

Wang, Yi-Hsuan; Young, Shelley Shwu-Ching

2014-01-01

The purpose of the study is to explore and describe how to implement a pedagogical ASR-based intelligent computer-assisted speaking learning (iCASL) system to support adult learners with a private, flexible and individual learning environment to practice English pronunciation. The iCASL system integrates multiple levels of corrective feedback and…

Implementation Fest: The Last Decade

DTIC Science & Technology

2010-08-01

architectures New Learning Technologies  Simulations, games, and virtual world  Mobile systems  Performance support, S1000D tech manuals  Intelligent...Darwars Ambush (ECS) Gator 6 (Will Interactive) Games Today 22 VBS2 Enhanced Learning Environment using Creative Technology – Bilateral Negotiations...5f. WORK UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Advanced Decision Learning (ADL),1901 N. Beauregard Street Suite 600

Architecture for Multiple Interacting Robot Intelligences

NASA Technical Reports Server (NTRS)

Peters, Richard Alan, II (Inventor)

2008-01-01

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a database associative memory (DBAM) that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Intelligent deflection routing in buffer-less networks.

PubMed

Haeri, Soroush; Trajković, Ljiljana

2015-02-01

Deflection routing is employed to ameliorate packet loss caused by contention in buffer-less architectures such as optical burst-switched networks. The main goal of deflection routing is to successfully deflect a packet based only on a limited knowledge that network nodes possess about their environment. In this paper, we present a framework that introduces intelligence to deflection routing (iDef). iDef decouples the design of the signaling infrastructure from the underlying learning algorithm. It consists of a signaling and a decision-making module. Signaling module implements a feedback management protocol while the decision-making module implements a reinforcement learning algorithm. We also propose several learning-based deflection routing protocols, implement them in iDef using the ns-3 network simulator, and compare their performance.

Opportunistic Behavior in Motivated Learning Agents.

PubMed

Graham, James; Starzyk, Janusz A; Jachyra, Daniel

2015-08-01

This paper focuses on the novel motivated learning (ML) scheme and opportunistic behavior of an intelligent agent. It extends previously developed ML to opportunistic behavior in a multitask situation. Our paper describes the virtual world implementation of autonomous opportunistic agents learning in a dynamically changing environment, creating abstract goals, and taking advantage of arising opportunities to improve their performance. An opportunistic agent achieves better results than an agent based on ML only. It does so by minimizing the average value of all need signals rather than a dominating need. This paper applies to the design of autonomous embodied systems (robots) learning in real-time how to operate in a complex environment.

Beyond adaptive-critic creative learning for intelligent mobile robots

NASA Astrophysics Data System (ADS)

Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

2001-10-01

Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it permits the discovery of the unknown problems, ones that are not yet recognized but may be critical to survival or success.

Intelligible machine learning with malibu.

PubMed

Langlois, Robert E; Lu, Hui

2008-01-01

malibu is an open-source machine learning work-bench developed in C/C++ for high-performance real-world applications, namely bioinformatics and medical informatics. It leverages third-party machine learning implementations for more robust bug-free software. This workbench handles several well-studied supervised machine learning problems including classification, regression, importance-weighted classification and multiple-instance learning. The malibu interface was designed to create reproducible experiments ideally run in a remote and/or command line environment. The software can be found at: http://proteomics.bioengr. uic.edu/malibu/index.html.

Multidimensional Learner Model In Intelligent Learning System

NASA Astrophysics Data System (ADS)

Deliyska, B.; Rozeva, A.

2009-11-01

The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

The influence of active vision on the exoskeleton of intelligent agents

NASA Astrophysics Data System (ADS)

Smith, Patrice; Terry, Theodore B.

2016-04-01

Chameleonization occurs when a self-learning autonomous mobile system's (SLAMR) active vision scans the surface of which it is perched causing the exoskeleton to changes colors exhibiting a chameleon effect. Intelligent agents having the ability to adapt to their environment and exhibit key survivability characteristics of its environments would largely be due in part to the use of active vision. Active vision would allow the intelligent agent to scan its environment and adapt as needed in order to avoid detection. The SLAMR system would have an exoskeleton, which would change, based on the surface it was perched on; this is known as the "chameleon effect." Not in the common sense of the term, but from the techno-bio inspired meaning as addressed in our previous paper. Active vision, utilizing stereoscopic color sensing functionality would enable the intelligent agent to scan an object within its close proximity, determine the color scheme, and match it; allowing the agent to blend with its environment. Through the use of its' optical capabilities, the SLAMR system would be able to further determine its position, taking into account spatial and temporal correlation and spatial frequency content of neighboring structures further ensuring successful background blending. The complex visual tasks of identifying objects, using edge detection, image filtering, and feature extraction are essential for an intelligent agent to gain additional knowledge about its environmental surroundings.

Metacognitive Support Promotes an Effective Use of Instructional Resources in Intelligent Tutoring

ERIC Educational Resources Information Center

Schwonke, Rolf; Ertelt, Anna; Otieno, Christine; Renkl, Alexander; Aleven, Vincent; Salden, Ron J. C. M.

2013-01-01

We tested whether the provision of metacognitive knowledge on how to cope with the complexity of a learning environment improved learning. In an experimental setting, high-school students (N = 60) worked through a computer-based geometry lesson either with or without metacognitive support in the form of a cue card. This cue card encouraged…

An Exploration of "Scaffolded" and "Experiential" Learning Environment's Impact upon Students' Experiences of a Challenging Level 6 Topic in Forensic Psychology: MAPPA

ERIC Educational Resources Information Center

Wilkinson, Dean J.; Jones, Tim

2017-01-01

Higher education institutions want to develop rounded, independent learners equipped with the required skills to embrace the challenges of post-graduation (European Commission, 2013). Vygotsky suggests learners are interdependent, born as social beings with emotional intelligence. Experiential learning is created by direct participation in life…

Learning Intercultural Communication Skills with Virtual Humans: Feedback and Fidelity

ERIC Educational Resources Information Center

Lane, H. Chad; Hays, Matthew Jensen; Core, Mark G.; Auerbach, Daniel

2013-01-01

In the context of practicing intercultural communication skills, we investigated the role of fidelity in a game-based, virtual learning environment as well as the role of feedback delivered by an intelligent tutoring system. In 2 experiments, we compared variations on the game interface, use of the tutoring system, and the form of the feedback.…

The achievement of spacecraft autonomy through the thematic application of multiple cooperating intelligent agents

NASA Technical Reports Server (NTRS)

Rossomando, Philip J.

1992-01-01

A description is given of UNICORN, a prototype system developed for the purpose of investigating artificial intelligence (AI) concepts supporting spacecraft autonomy. UNICORN employs thematic reasoning, of the type first described by Rodger Schank of Northwestern University, to allow the context-sensitive control of multiple intelligent agents within a blackboard based environment. In its domain of application, UNICORN demonstrates the ability to reason teleologically with focused knowledge. Also presented are some of the lessons learned as a result of this effort. These lessons apply to any effort wherein system level autonomy is the objective.

A novel data-driven learning method for radar target detection in nonstationary environments

DOE PAGES

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

2016-04-12

Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata

Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less

Self-Learning Embedded System for Object Identification in Intelligent Infrastructure Sensors.

PubMed

Villaverde, Monica; Perez, David; Moreno, Felix

2015-11-17

The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.

A BDI Approach to Infer Student's Emotions in an Intelligent Learning Environment

ERIC Educational Resources Information Center

Jaques, Patricia Augustin; Vicari, Rosa Maria

2007-01-01

In this article we describe the use of mental states approach, more specifically the belief-desire-intention (BDI) model, to implement the process of affective diagnosis in an educational environment. We use the psychological OCC model, which is based on the cognitive theory of emotions and is possible to be implemented computationally, in order…

Intelligence Community Forum

DTIC Science & Technology

2008-11-05

Description Operationally Feasible? EEG ms ms cm Measures electrical activity in the brain. Practical tool for applications - real time monitoring or...Cognitive Systems Device Development & Processing Methods Brain activity can be monitored in real-time in operational environments with EEG Brain...biological and cognitive findings about the user to customize the learning environment Neurofeedback • Present the user with real-time feedback

Enhancing Computer Science Education with a Wireless Intelligent Simulation Environment

ERIC Educational Resources Information Center

Cook, Diane J.; Huber, Manfred; Yerraballi, Ramesh; Holder, Lawrence B.

2004-01-01

The goal of this project is to develop a unique simulation environment that can be used to increase students' interest and expertise in Computer Science curriculum. Hands-on experience with physical or simulated equipment is an essential ingredient for learning, but many approaches to training develop a separate piece of equipment or software for…

Spontaneous Group Learning in Ambient Learning Environments

NASA Astrophysics Data System (ADS)

Bick, Markus; Jughardt, Achim; Pawlowski, Jan M.; Veith, Patrick

Spontaneous Group Learning is a concept to form and facilitate face-to-face, ad-hoc learning groups in collaborative settings. We show how to use Ambient Intelligence to identify, support, and initiate group processes. Learners' positions are determined by widely used technologies, e.g., Bluetooth and WLAN. As a second step, learners' positions, tasks, and interests are visualized. Finally, a group process is initiated supported by relevant documents and services. Our solution is a starting point to develop new didactical solutions for collaborative processes.

A Common Cockpit Training System

DTIC Science & Technology

2005-01-01

a learning environment where students can practice ASW via free - play simulated tactical situations while receiving feedback and instruction customized...Mission Display and includes free play simulation capability to maximize training. This intelligent tutoring system (ITS) will observe the operator’s

Multi-objects recognition for distributed intelligent sensor networks

NASA Astrophysics Data System (ADS)

He, Haibo; Chen, Sheng; Cao, Yuan; Desai, Sachi; Hohil, Myron E.

2008-04-01

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Intelligent judgements over health risks in a spatial agent-based model.

PubMed

Abdulkareem, Shaheen A; Augustijn, Ellen-Wien; Mustafa, Yaseen T; Filatova, Tatiana

2018-03-20

Millions of people worldwide are exposed to deadly infectious diseases on a regular basis. Breaking news of the Zika outbreak for instance, made it to the main media titles internationally. Perceiving disease risks motivate people to adapt their behavior toward a safer and more protective lifestyle. Computational science is instrumental in exploring patterns of disease spread emerging from many individual decisions and interactions among agents and their environment by means of agent-based models. Yet, current disease models rarely consider simulating dynamics in risk perception and its impact on the adaptive protective behavior. Social sciences offer insights into individual risk perception and corresponding protective actions, while machine learning provides algorithms and methods to capture these learning processes. This article presents an innovative approach to extend agent-based disease models by capturing behavioral aspects of decision-making in a risky context using machine learning techniques. We illustrate it with a case of cholera in Kumasi, Ghana, accounting for spatial and social risk factors that affect intelligent behavior and corresponding disease incidents. The results of computational experiments comparing intelligent with zero-intelligent representations of agents in a spatial disease agent-based model are discussed. We present a spatial disease agent-based model (ABM) with agents' behavior grounded in Protection Motivation Theory. Spatial and temporal patterns of disease diffusion among zero-intelligent agents are compared to those produced by a population of intelligent agents. Two Bayesian Networks (BNs) designed and coded using R and are further integrated with the NetLogo-based Cholera ABM. The first is a one-tier BN1 (only risk perception), the second is a two-tier BN2 (risk and coping behavior). We run three experiments (zero-intelligent agents, BN1 intelligence and BN2 intelligence) and report the results per experiment in terms of several macro metrics of interest: an epidemic curve, a risk perception curve, and a distribution of different types of coping strategies over time. Our results emphasize the importance of integrating behavioral aspects of decision making under risk into spatial disease ABMs using machine learning algorithms. This is especially relevant when studying cumulative impacts of behavioral changes and possible intervention strategies.

Intelligent robot trends and predictions for the .net future

NASA Astrophysics Data System (ADS)

Hall, Ernest L.

2001-10-01

An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. The use of these machines in factory automation can improve productivity, increase product quality and improve competitiveness. This paper presents a discussion of recent and future technical and economic trends. During the past twenty years the use of industrial robots that are equipped not only with precise motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. Intelligent robot products have been developed in many cases for factory automation and for some hospital and home applications. To reach an even higher degree of applications, the addition of learning may be required. Recently, learning theories such as the adaptive critic have been proposed. In this type of learning, a critic provides a grade to the controller of an action module such as a robot. The adaptive critic is a good model for human learning. In general, the critic may be considered to be the human with the teach pendant, plant manager, line supervisor, quality inspector or the consumer. If the ultimate critic is the consumer, then the quality inspector must model the consumer's decision-making process and use this model in the design and manufacturing operations. Can the adaptive critic be used to advance intelligent robots? Intelligent robots have historically taken decades to be developed and reduced to practice. Methods for speeding this development include technology such as rapid prototyping and product development and government, industry and university cooperation.

Evolutionary Intelligence and Communication in Societies of Virtually Embodied Agents

NASA Astrophysics Data System (ADS)

Nguyen, Binh; Skabar, Andrew

In order to overcome the knowledge bottleneck problem, AI researchers have attempted to develop systems that are capable of automated knowledge acquisition. However, learning in these systems is hindered by context (i.e., symbol-grounding) problems, which are caused by the systems lacking the unifying structure of bodies, situations and needs that typify human learning. While the fields of Embodied Artificial Intelligence and Artificial Life have come a long way towards demonstrating how artificial systems can develop knowledge of the physical and social worlds, the focus in these areas has been on low level intelligence, and it is not clear how, such systems can be extended to deal with higher-level knowledge. In this paper, we argue that we can build towards a higher level intelligence by framing the problem as one of stimulating the development of culture and language. Specifically, we identify three important limitations that face the development of culture and language in AI systems, and propose how these limitations can be overcome. We will do this through borrowing ideas from the evolutionary sciences, which have explored how interactions between embodiment and environment have shaped the development of human intelligence and knowledge.

The effect of learning style on academic student success

NASA Astrophysics Data System (ADS)

Stackhouse, Omega N.

The problem addressed in this study was that little was known about the impact on student academic achievement, when grouped by learning style, in a multiple intelligence based science curriculum. The larger problem was that many students were frequently unengaged and, consequently, low achieving in their science courses. This quantitative study used an ex post facto research design to better understand the impact of student learning style on the academic success of students in a Multiple Intelligence Theory based course room. Gardner's work on Multiple Intelligence served as the conceptual framework for this study. The research question for this study asked if academic instruction that employs multiple intelligence theories has a relationship with students' academic achievement differently according to their learning style group (auditory, visual, and kinesthetic). Existing data from 85 students were placed into 1 of 3 groups: (a) Auditory, (b) Visual, or (c) Kinesthetic Learning Style) using existing data from a student inventory instrument. The independent variable was existing data from student inventories of learning style and the dependent variable was existing student scores from the Physical Science End of Course Test. Existing data were taken from students that were all taught with the same strategies in similar classroom environments. The Physical Science End of Course Test was developed with stringent measures to protect validity by the developer, McGraw-Hill. Cronbach's Alpha was conducted to determine the internal reliability coefficient of the student inventory. The impact for social change is that adding to the body of knowledge regarding student learning style and science curriculum provides valuable information for teachers, administrators, and school policy makers. This will allow teachers to better prepare to engage their students' and to prepare them for their place in society.

Intelligent tuning method of PID parameters based on iterative learning control for atomic force microscopy.

PubMed

Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang

2018-01-01

Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Learning comunication strategies for distributed artificial intelligence

NASA Astrophysics Data System (ADS)

Kinney, Michael; Tsatsoulis, Costas

1992-08-01

We present a methodology that allows collections of intelligent system to automatically learn communication strategies, so that they can exchange information and coordinate their problem solving activity. In our methodology communication between agents is determined by the agents themselves, which consider the progress of their individual problem solving activities compared to the communication needs of their surrounding agents. Through learning, communication lines between agents might be established or disconnected, communication frequencies modified, and the system can also react to dynamic changes in the environment that might force agents to cease to exist or to be added. We have established dynamic, quantitative measures of the usefulness of a fact, the cost of a fact, the work load of an agent, and the selfishness of an agent (a measure indicating an agent's preference between transmitting information versus performing individual problem solving), and use these values to adapt the communication between intelligent agents. In this paper we present the theoretical foundations of our work together with experimental results and performance statistics of networks of agents involved in cooperative problem solving activities.

Projective simulation for artificial intelligence

NASA Astrophysics Data System (ADS)

Briegel, Hans J.; de Las Cuevas, Gemma

2012-05-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.

Projective simulation for artificial intelligence

PubMed Central

Briegel, Hans J.; De las Cuevas, Gemma

2012-01-01

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation. PMID:22590690

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Duda, R. O.; Fikes, R. E.; Hart, P. E.; Nilsson, N. J.; Thorndyke, P. W.; Wilber, B. M.

1971-01-01

Research in the field of artificial intelligence is discussed. The focus of recent work has been the design, implementation, and integration of a completely new system for the control of a robot that plans, learns, and carries out tasks autonomously in a real laboratory environment. The computer implementation of low-level and intermediate-level actions; routines for automated vision; and the planning, generalization, and execution mechanisms are reported. A scenario that demonstrates the approximate capabilities of the current version of the entire robot system is presented.

Autonomous operations through onboard artificial intelligence

NASA Technical Reports Server (NTRS)

Sherwood, R. L.; Chien, S.; Castano, R.; Rabideau, G.

2002-01-01

The Autonomous Sciencecraft Experiment (ASE) will fly onboard the Air Force TechSat 21 constellation of three spacecraft scheduled for launch in 2006. ASE uses onboard continuous planning, robust task and goal-based execution, model-based mode identification and reconfiguration, and onboard machine learning and pattern recognition to radically increase science return by enabling intelligent downlink selection and autonomous retargeting. Demonstration of these capabilities in a flight environment will open up tremendous new opportunities in planetary science, space physics, and earth science that would be unreachable without this technology.

Experimentation of cooperative learning model Numbered Heads Together (NHT) type by concept maps and Teams Games Tournament (TGT) by concept maps in terms of students logical mathematics intellegences

NASA Astrophysics Data System (ADS)

Irawan, Adi; Mardiyana; Retno Sari Saputro, Dewi

2017-06-01

This research is aimed to find out the effect of learning model towards learning achievement in terms of students’ logical mathematics intelligences. The learning models that were compared were NHT by Concept Maps, TGT by Concept Maps, and Direct Learning model. This research was pseudo experimental by factorial design 3×3. The population of this research was all of the students of class XI Natural Sciences of Senior High School in all regency of Karanganyar in academic year 2016/2017. The conclusions of this research were: 1) the students’ achievements with NHT learning model by Concept Maps were better than students’ achievements with TGT model by Concept Maps and Direct Learning model. The students’ achievements with TGT model by Concept Maps were better than the students’ achievements with Direct Learning model. 2) The students’ achievements that exposed high logical mathematics intelligences were better than students’ medium and low logical mathematics intelligences. The students’ achievements that exposed medium logical mathematics intelligences were better than the students’ low logical mathematics intelligences. 3) Each of student logical mathematics intelligences with NHT learning model by Concept Maps has better achievement than students with TGT learning model by Concept Maps, students with NHT learning model by Concept Maps have better achievement than students with the direct learning model, and the students with TGT by Concept Maps learning model have better achievement than students with Direct Learning model. 4) Each of learning model, students who have logical mathematics intelligences have better achievement then students who have medium logical mathematics intelligences, and students who have medium logical mathematics intelligences have better achievement than students who have low logical mathematics intelligences.

Multiple Intelligence and Digital Learning Awareness of Prospective B.Ed Teachers

ERIC Educational Resources Information Center

Gracious, F. L. Antony; Shyla, F. L. Jasmine Anne

2012-01-01

The present study Multiple Intelligence and Digital Learning Awareness of prospective B.Ed teachers was probed to find the relationship between Multiple Intelligence and Digital Learning Awareness of Prospective B.Ed Teachers. Data for the study were collected using self made Multiple Intelligence Inventory and Digital Learning Awareness Scale.…

Cooperative learning model with high order thinking skills questions: an understanding on geometry

NASA Astrophysics Data System (ADS)

Sari, P. P.; Budiyono; Slamet, I.

2018-05-01

Geometry, a branch of mathematics, has an important role in mathematics learning. This research aims to find out the effect of learning model, emotional intelligence, and the interaction between learning model and emotional intelligence toward students’ mathematics achievement. This research is quasi-experimental research with 2 × 3 factorial design. The sample in this research included 179 Senior High School students on 11th grade in Sukoharjo Regency, Central Java, Indonesia in academic year of 2016/2017. The sample was taken by using stratified cluster random sampling. The results showed that: the student are taught by Thinking Aloud Pairs Problem-Solving using HOTs questions provides better mathematics learning achievement than Make A Match using HOTs questions. High emotional intelligence students have better mathematics learning achievement than moderate and low emotional intelligence students, and moderate emotional intelligence students have better mathematics learning achievement than low emotional intelligence students. There is an interaction between learning model and emotional intelligence, and these affect mathematics learning achievement. We conclude that appropriate learning model can support learning activities become more meaningful and facilitate students to understand material. For further research, we suggest to explore the contribution of other aspects in cooperative learning modification to mathematics achievement.

Design and Implementation of C-iLearning: A Cloud-Based Intelligent Learning System

ERIC Educational Resources Information Center

Xiao, Jun; Wang, Minjuan; Wang, Lamei; Zhu, Xiaoxiao

2013-01-01

The gradual development of intelligent learning (iLearning) systems has prompted the changes of teaching and learning. This paper presents the architecture of an intelligent learning (iLearning) system built upon the recursive iLearning model and the key technologies associated with this model. Based on this model and the technical structure of a…

Homeostatic Agent for General Environment

NASA Astrophysics Data System (ADS)

Yoshida, Naoto

2018-03-01

One of the essential aspect in biological agents is dynamic stability. This aspect, called homeostasis, is widely discussed in ethology, neuroscience and during the early stages of artificial intelligence. Ashby's homeostats are general-purpose learning machines for stabilizing essential variables of the agent in the face of general environments. However, despite their generality, the original homeostats couldn't be scaled because they searched their parameters randomly. In this paper, first we re-define the objective of homeostats as the maximization of a multi-step survival probability from the view point of sequential decision theory and probabilistic theory. Then we show that this optimization problem can be treated by using reinforcement learning algorithms with special agent architectures and theoretically-derived intrinsic reward functions. Finally we empirically demonstrate that agents with our architecture automatically learn to survive in a given environment, including environments with visual stimuli. Our survival agents can learn to eat food, avoid poison and stabilize essential variables through theoretically-derived single intrinsic reward formulations.

Provision of Training for the IT Industry: The ELEVATE Project

NASA Astrophysics Data System (ADS)

Paraskakis, Iraklis; Konstantinidis, Andreas; Bouras, Thanassis; Perakis, Kostas; Pantelopoulos, Stelios; Hatziapostolou, Thanos

This paper will present ELEVATE that aims to deliver an innovative training, educational and certification environment integrating the application software to be taught with the training procedure. ELEVATE aspires to address the training needs of software development SMEs and the solution proposed is based on three basic notions: to provide competence training that is tailored to the needs of the individual trainee, to allow the trainee to carry out authentic activities as well as problem based learning that draws from real life scenarios and finally to allow for the assessment and certification of the skills and competences acquired. In order to achieve the desired results the ELEVATE architecture utilises an Interactive Interoperability Layer, an Intelligent Personalization Trainer as well as the Training, Evaluation & Certification component. As an end product, the ELEVATE project The ELEVATE pedagogical model is based on blended learning, the e-Training component (an intelligent system that provides tailored training) and Learning 2.0.

Machine learning based Intelligent cognitive network using fog computing

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik

2017-05-01

In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

NASA Astrophysics Data System (ADS)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

Learning Disabilities and Emotional Intelligence.

PubMed

Zysberg, Leehu; Kasler, Jon

2017-07-04

The literature is conflicted around the subject of the emotional abilities of individuals with Specific Learning Disabilities (SLDs): While many claim cognitive challenges are associated with emotional difficulties, some suggest emotional and interpersonal abilities are not compromised in such disorders and may help individuals compensate and cope effectively with the challenges they meet in learning environments. Two studies explored differences in emotional intelligence (EI) between young adults with and without SLD. Two samples (matched on gender, approximate age, and program of study; n = 100, and unmatched; n = 584) of college students took self-report and performance-based tests of EI (Ability-EI) as well as a measure of self-esteem and demographics associated with college performance (e.g.: SAT scores, gender, etc.). The results showed that while SAT scores and ability emotional intelligence (Ability-EI) were associated with college GPA, Ability-EI did not differ between the two groups, while self-report measures of EI and self-esteem did show differences, with the group with learning disabilities ranking lower. The effects remained stable when we controlled for demographics and potential intervening factors. The results suggest that EI may play a protective role in the association between background variables and college attainment in students with SLD. The results may provide a basis for interventions to empower students with SLD in academia.

Evaluating the relation between memory and intelligence in children with learning disabilities.

PubMed

Hoerig, Dianne C; David, Andrew S; D'Amato, Rik Carl

2002-12-01

Although both intelligence tests and memory tests are commonly used in neuropsychological examinations, the relationship between memory and intelligence has not been fully explored, particularly for children having learning disabilities. Memory, or the ability to retain information, was evaluated using the Test of Memory and Learning, a recently released test that gives a comprehensive measure of global memory functioning. This, and the Wechsler Intelligence Scale for Children-Third Edition, used to assess intelligence, were given to 80 students with learning disabilities. The correlation between a global measure of memory and a global measure f intelligence was significant (r = .59), indicating that memory should be viewed as an important component when evaluating children with learning disabilities.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri vocational school students

NASA Astrophysics Data System (ADS)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-05-01

This study aims to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students' mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

The experimentation of LC7E learning model on the linear program material in terms of interpersonal intelligence on Wonogiri Vocational School students

NASA Astrophysics Data System (ADS)

Antinah; Kusmayadi, T. A.; Husodo, B.

2018-03-01

This study aimed to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students’ mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.

Meeting People's Needs in a Fully Interoperable Domotic Environment

PubMed Central

Miori, Vittorio; Russo, Dario; Concordia, Cesare

2012-01-01

The key idea underlying many Ambient Intelligence (AmI) projects and applications is context awareness, which is based mainly on their capacity to identify users and their locations. The actual computing capacity should remain in the background, in the periphery of our awareness, and should only move to the center if and when necessary. Computing thus becomes ‘invisible’, as it is embedded in the environment and everyday objects. The research project described herein aims to realize an Ambient Intelligence-based environment able to improve users' quality of life by learning their habits and anticipating their needs. This environment is part of an adaptive, context-aware framework designed to make today's incompatible heterogeneous domotic systems fully interoperable, not only for connecting sensors and actuators, but for providing comprehensive connections of devices to users. The solution is a middleware architecture based on open and widely recognized standards capable of abstracting the peculiarities of underlying heterogeneous technologies and enabling them to co-exist and interwork, without however eliminating their differences. At the highest level of this infrastructure, the Ambient Intelligence framework, integrated with the domotic sensors, can enable the system to recognize any unusual or dangerous situations and anticipate health problems or special user needs in a technological living environment, such as a house or a public space. PMID:22969322

Meeting people's needs in a fully interoperable domotic environment.

PubMed

Miori, Vittorio; Russo, Dario; Concordia, Cesare

2012-01-01

The key idea underlying many Ambient Intelligence (AmI) projects and applications is context awareness, which is based mainly on their capacity to identify users and their locations. The actual computing capacity should remain in the background, in the periphery of our awareness, and should only move to the center if and when necessary. Computing thus becomes 'invisible', as it is embedded in the environment and everyday objects. The research project described herein aims to realize an Ambient Intelligence-based environment able to improve users' quality of life by learning their habits and anticipating their needs. This environment is part of an adaptive, context-aware framework designed to make today's incompatible heterogeneous domotic systems fully interoperable, not only for connecting sensors and actuators, but for providing comprehensive connections of devices to users. The solution is a middleware architecture based on open and widely recognized standards capable of abstracting the peculiarities of underlying heterogeneous technologies and enabling them to co-exist and interwork, without however eliminating their differences. At the highest level of this infrastructure, the Ambient Intelligence framework, integrated with the domotic sensors, can enable the system to recognize any unusual or dangerous situations and anticipate health problems or special user needs in a technological living environment, such as a house or a public space.

SuperSchools: Education in the Information Age and Beyond.

ERIC Educational Resources Information Center

Ameritech Foundation, Chicago, IL.

This document discusses how improvements in the capabilities of the intelligent communications network are making new enhancements and advances available to educators, administrators, students, parents, and the community, focusing on the role of Ameritech. Modern technologies can create dynamic and appropriate learning environments for children…

Semantic Social Scaffolding for Capturing and Sharing Dissertation Experience

ERIC Educational Resources Information Center

Dimitrova, V.; Lau, L.; O'Rourke, R.

2011-01-01

This paper presents a novel collaborative tool--AWESOME Dissertation Environment (ADE)--which facilitates student learning through semantic social scaffolding: a new approach to dissertation writing challenges. These challenges revolve around three issues: timing of support; collective intelligence, and sense making strategies in tension with the…

DCG & GTE: Dynamic Courseware Generation with Teaching Expertise.

ERIC Educational Resources Information Center

Vassileva, Julita

1998-01-01

Discusses the place of GTE (Generic Tutoring Environment) as an approach to bridging the gap between computer-assisted learning and intelligent tutoring systems; describes DCG (dynamic courseware generation) which allows dynamic planning of the contents of an instructional course; and considers combining GTE with DCG. (Author/LRW)

The Effect Of The Materials Based On Multiple Intelligence Theory Upon The Intelligence Groups' Learning Process

NASA Astrophysics Data System (ADS)

Oral, I.; Dogan, O.

2007-04-01

The aim of this study is to find out the effect of the course materials based on Multiple Intelligence Theory upon the intelligence groups' learning process. In conclusion, the results proved that the materials prepared according to Multiple Intelligence Theory have a considerable effect on the students' learning process. This effect was particularly seen on the student groups of the musical-rhythmic, verbal-linguistic, interpersonal-social and naturalist intelligence.

Why are women so intelligent? The effect of maternal IQ on childhood mortality may be a relevant evolutionary factor.

PubMed

Charlton, Bruce G

2010-03-01

Humans are an unusual species because they exhibit an economic division of labour. Most theories concerning the evolution of specifically human intelligence have focused either on economic problems or sexual selection mechanisms, both of which apply more to men than women. Yet while there is evidence for men having a slightly higher average IQ, the sexual dimorphism of intelligence is not obvious (except at unusually high and low levels). However, a more female-specific selection mechanism concerns the distinctive maternal role in child care during the offspring's early years. It has been reported that increasing maternal intelligence is associated with reducing child mortality. This would lead to a greater level of reproductive success for intelligent women, and since intelligence is substantially heritable, this is a plausible mechanism by which natural selection might tend to increase female intelligence in humans. Any effect of maternal intelligence on improving child survival would likely be amplified by assortative mating for IQ by which people tend to marry others of similar intelligence - combining female maternal and male economic or sexual selection factors. Furthermore, since general intelligence seems to have the functional attribute of general purpose problem-solving and more rapid learning, the advantages of maternal IQ are likely to be greater as the environment for child-rearing is more different from the African hunter-gatherer society and savannah environment in which ancestral humans probably evolved. However, the effect of maternal IQ on child mortality would probably only be of major evolutionary significance in environments where childhood mortality rates were high. The modern situation is that population growth is determined mostly by birth rates; so in modern conditions, maternal intelligence may no longer have a significant effect on reproductive success; the effect of female IQ on reproductive success is often negative. Nonetheless, in the past it is plausible that the link between maternal IQ and child survival constituted a strong selection pressure acting specifically on women. Copyright (c) 2009. Published by Elsevier Ltd.

Intelligent Sensing in Dynamic Environments Using Markov Decision Process

PubMed Central

Nanayakkara, Thrishantha; Halgamuge, Malka N.; Sridhar, Prasanna; Madni, Asad M.

2011-01-01

In a network of low-powered wireless sensors, it is essential to capture as many environmental events as possible while still preserving the battery life of the sensor node. This paper focuses on a real-time learning algorithm to extend the lifetime of a sensor node to sense and transmit environmental events. A common method that is generally adopted in ad-hoc sensor networks is to periodically put the sensor nodes to sleep. The purpose of the learning algorithm is to couple the sensor’s sleeping behavior to the natural statistics of the environment hence that it can be in optimal harmony with changes in the environment, the sensors can sleep when steady environment and stay awake when turbulent environment. This paper presents theoretical and experimental validation of a reward based learning algorithm that can be implemented on an embedded sensor. The key contribution of the proposed approach is the design and implementation of a reward function that satisfies a trade-off between the above two mutually contradicting objectives, and a linear critic function to approximate the discounted sum of future rewards in order to perform policy learning. PMID:22346624

Art of War Papers: An Exit Strategy not a Winning Strategy? Intelligence Lessons Learned from the British Emergency in South Arabia, 1963-67

DTIC Science & Technology

2014-04-01

addition to the above Art of War team, I was very fortunate to have support from Professor Daniel Marston, the author Mr Jonathan Walker, Brigadier...Sincere thanks to all; nonetheless, all errors and omissions are my own. Finally, I must pay tribute to all the British Servicemen, and Policemen, who...militar- ies —especially in the field of intelligence in a hostile environment. The war in South Arabia was fought by a western force with local allies

A Career Guidance Curriculum for Ninth Grade Students. Occupational Cluster Learning Activities. Business-Environmental. Part 1 of 2. Ninth Grade Guidance Project. Project Duration: July 16, 1979, to June 30, 1980.

ERIC Educational Resources Information Center

Cape May County Vocational Schools, NJ.

This first of two parts presents learning activities for four occupational clusters of a ninth-grade cluster program. It contains theory and hands-on activities that explore the occupational requirements and working environment of these areas to help students make intelligent decisions of possible career choices based on levels of interest and…

Progressions of Qualitative Models as a Foundation for Intelligent Learning Environments

DTIC Science & Technology

1986-05-01

knowledge form is that in addition to being efficient and powerul knowledge structures for studeiis to possess, they are also efficient and powerful ...reason "on their feet" about circuit behavibr, and is potentially a very powerful instructional task. Conventionally, however, troubleshooting is preceded...also be applied to a light bulb. 4. Kowledge differentiation -- The student learns about the differences &1 r 41 between two concepts. For instance

The effect of learning models and emotional intelligence toward students learning outcomes on reaction rate

NASA Astrophysics Data System (ADS)

Sutiani, Ani; Silitonga, Mei Y.

2017-08-01

This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.

My Science Tutor: A Conversational Multimedia Virtual Tutor

ERIC Educational Resources Information Center

Ward, Wayne; Cole, Ron; Bolaños, Daniel; Buchenroth-Martin, Cindy; Svirsky, Edward; Weston, Tim

2013-01-01

My Science Tutor (MyST) is an intelligent tutoring system designed to improve science learning by elementary school students through conversational dialogs with a virtual science tutor in an interactive multimedia environment. Marni, a lifelike 3-D character, engages individual students in spoken dialogs following classroom investigations using…

Analytic Hierarchy Process for Personalising Environmental Information

ERIC Educational Resources Information Center

Kabassi, Katerina

2014-01-01

This paper presents how a Geographical Information System (GIS) can be incorporated in an intelligent learning software system for environmental matters. The system is called ALGIS and incorporates the GIS in order to present effectively information about the physical and anthropogenic environment of Greece in a more interactive way. The system…

Supporting Effective Collaboration: Using a Rearview Mirror to Look Forward

ERIC Educational Resources Information Center

McManus, Margaret M.; Aiken, Robert M.

2016-01-01

Our original research, to design and develop an Intelligent Collaborative Learning System (ICLS), yielded the creation of a Group Leader Tutor software system which utilizes a Collaborative Skills Network to monitor students working collaboratively in a networked environment. The Collaborative Skills Network was a conceptualization of…

Applying AI to the Writer's Learning Environment.

ERIC Educational Resources Information Center

Houlette, Forrest

1991-01-01

Discussion of current applications of artificial intelligence (AI) to writing focuses on how to represent knowledge of the writing process in a way that links procedural knowledge to other types of knowledge. A model is proposed that integrates the subtasks of writing into the process of writing itself. (15 references) (LRW)

Intelligent Tutors in Immersive Virtual Environments

ERIC Educational Resources Information Center

Yan, Peng; Slator, Brian M.; Vender, Bradley; Jin, Wei; Kariluoma, Matti; Borchert, Otto; Hokanson, Guy; Aggarwal, Vaibhav; Cosmano, Bob; Cox, Kathleen T.; Pilch, André; Marry, Andrew

2013-01-01

Research into virtual role-based learning has progressed over the past decade. Modern issues include gauging the difficulty of designing a goal system capable of meeting the requirements of students with different knowledge levels, and the reasonability and possibility of taking advantage of the well-designed formula and techniques served in other…

Dynamic User Modeling within a Game-Based ITS

ERIC Educational Resources Information Center

Snow, Erica L.

2015-01-01

Intelligent tutoring systems are adaptive learning environments designed to support individualized instruction. The adaptation embedded within these systems is often guided by user models that represent one or more aspects of students' domain knowledge, actions, or performance. The proposed project focuses on the development and testing of user…

Intelligent Computer-Assisted Language Learning.

ERIC Educational Resources Information Center

Harrington, Michael

1996-01-01

Introduces the field of intelligent computer assisted language learning (ICALL) and relates them to current practice in computer assisted language learning (CALL) and second language learning. Points out that ICALL applies expertise from artificial intelligence and the computer and cognitive sciences to the development of language learning…

A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems

DTIC Science & Technology

1990-11-01

Intelligence Systems," in Distributed Artifcial Intelligence , vol. II, L. Gasser and M. Huhns (eds), Pitman, London, 1989, pp. 413-430. Shaw, M. Harrow, B...IDTIC FILE COPY A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems N Michael I. Shaw...SUBTITLE 5. FUNDING NUMBERS A Distributed Problem-Solving Approach to Rule Induction: Learning in Distributed Artificial Intelligence Systems 6

Emerging Approach of Natural Language Processing in Opinion Mining: A Review

NASA Astrophysics Data System (ADS)

Kim, Tai-Hoon

Natural language processing (NLP) is a subfield of artificial intelligence and computational linguistics. It studies the problems of automated generation and understanding of natural human languages. This paper outlines a framework to use computer and natural language techniques for various levels of learners to learn foreign languages in Computer-based Learning environment. We propose some ideas for using the computer as a practical tool for learning foreign language where the most of courseware is generated automatically. We then describe how to build Computer Based Learning tools, discuss its effectiveness, and conclude with some possibilities using on-line resources.

A multi-agent intelligent environment for medical knowledge.

PubMed

Vicari, Rosa M; Flores, Cecilia D; Silvestre, André M; Seixas, Louise J; Ladeira, Marcelo; Coelho, Helder

2003-03-01

AMPLIA is a multi-agent intelligent learning environment designed to support training of diagnostic reasoning and modelling of domains with complex and uncertain knowledge. AMPLIA focuses on the medical area. It is a system that deals with uncertainty under the Bayesian network approach, where learner-modelling tasks will consist of creating a Bayesian network for a problem the system will present. The construction of a network involves qualitative and quantitative aspects. The qualitative part concerns the network topology, that is, causal relations among the domain variables. After it is ready, the quantitative part is specified. It is composed of the distribution of conditional probability of the variables represented. A negotiation process (managed by an intelligent MediatorAgent) will treat the differences of topology and probability distribution between the model the learner built and the one built-in in the system. That negotiation process occurs between the agents that represent the expert knowledge domain (DomainAgent) and the agent that represents the learner knowledge (LearnerAgent).

Emotional Intelligence and Self-Directed Learning Readiness among College Students Participating in a Leadership Development Program

ERIC Educational Resources Information Center

Radnitzer, Karl David

2010-01-01

The purpose of this study was to investigate possible relationships between self-directed learning readiness and emotional intelligence in a leadership development program and if self-directed learning leads to greater self-directed learning capabilities. Prior research has examined self-directed learning and emotional intelligence but never have…

Implementation of Multiple Intelligences Supported Project-Based Learning in EFL/ESL Classrooms

ERIC Educational Resources Information Center

Bas, Gokhan

2008-01-01

This article deals with the implementation of Multiple Intelligences supported Project-Based learning in EFL/ESL Classrooms. In this study, after Multiple Intelligences supported Project-based learning was presented shortly, the implementation of this learning method into English classrooms. Implementation process of MI supported Project-based…

An Investigation between Multiple Intelligences and Learning Styles

ERIC Educational Resources Information Center

Sener, Sabriye; Çokçaliskan, Ayten

2018-01-01

Exploring learning style and multiple intelligence type of learners can enable the students to identify their strengths and weaknesses and learn from them. It is also very important for teachers to understand their learners' learning styles and multiple intelligences since they can carefully identify their goals and design activities that can…

Web-Based Intelligent E-Learning Systems: Technologies and Applications

ERIC Educational Resources Information Center

Ma, Zongmin

2006-01-01

Collecting and presenting the latest research and development results from the leading researchers in the field of e-learning systems, Web-Based Intelligent E-Learning Systems: Technologies and Applications provides a single record of current research and practical applications in Web-based intelligent e-learning systems. This book includes major…

Contributions Emotional Intelligence on Cognitive Learning Result of Biology of Senior High School Students in Medan, Indonesia

ERIC Educational Resources Information Center

Pratama, Anggi Tias; Corebima, Aloysius Duran

2016-01-01

Emotional intelligence is one of the factors affecting the success of students' learning results. Students having high emotional intelligence will be able to overcome the problems faced in school and in society. This research aims at investigating the correlation between emotional intelligence (EQ) and students' cognitive learning results of…

The Intelligent Behavior of Plants.

PubMed

van Loon, Leendert C

2016-04-01

Plants are as adept as animals and humans in reacting effectively to their ever-changing environment. Of necessity, their sessile nature requires specific adaptations, but their cells possess a network-type communication system with emerging properties at the level of the organ or entire plant. The specific adjustments in growth and development of plants can be taken to represent behavior. Their ability to learn from experience and to memorize previous experiences in order to optimize fitness allows effective acclimation to environmental stresses and can be considered a form of intelligence. Intelligent behavior is exemplified by the exceptional versatility of plants to deal with abiotic stresses as well as microbial and insect attack by balancing appropriate defensive reactions. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Convergence of Intelligences

NASA Astrophysics Data System (ADS)

Diederich, Joachim

Minsky (1985) argued an extraterrestrial intelligence may be similar to ours despite very different origins. ``Problem- solving'' offers evolutionary advantages and individuals who are part of a technical civilisation should have this capacity. On earth, the principles of problem-solving are the same for humans, some primates and machines based on Artificial Intelligence (AI) techniques. Intelligent systems use ``goals'' and ``sub-goals'' for problem-solving, with memories and representations of ``objects'' and ``sub-objects'' as well as knowledge of relations such as ``cause'' or ``difference.'' Some of these objects are generic and cannot easily be divided into parts. We must, therefore, assume that these objects and relations are universal, and a general property of intelligence. Minsky's arguments from 1985 are extended here. The last decade has seen the development of a general learning theory (``computational learning theory'' (CLT) or ``statistical learning theory'') which equally applies to humans, animals and machines. It is argued that basic learning laws will also apply to an evolved alien intelligence, and this includes limitations of what can be learned efficiently. An example from CLT is that the general learning problem for neural networks is intractable, i.e. it cannot be solved efficiently for all instances (it is ``NP-complete''). It is the objective of this paper to show that evolved intelligences will be constrained by general learning laws and will use task-decomposition for problem-solving. Since learning and problem-solving are core features of intelligence, it can be said that intelligences converge despite very different origins.

Vision Guided Intelligent Robot Design And Experiments

NASA Astrophysics Data System (ADS)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

A Career Guidance Curriculum for Ninth Grade Students. Occupational Cluster Learning Activities. Health-Technical. Part 2 of 2. Ninth Grade Career Guidance Project. Project Duration: July 16, 1979, to June 30, 1980.

ERIC Educational Resources Information Center

Cape May County Vocational Schools, NJ.

This second of two parts presents learning activities for four occupational clusters of a ninth-grade cluster program. It contains theory and hands-on activities that explore the occupational requirements and working environment of these areas to help students make intelligent decisions of possible career choices based on levels of interest and…

Information gathering, management and transfering for geospacial intelligence

NASA Astrophysics Data System (ADS)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-07-01

Information is a key subject in modern organization operations. The success of joint and combined operations with organizations partners depends on the accurate information and knowledge flow concerning the operations theatre: provision of resources, environment evolution, markets location, where and when an event occurred. As in the past and nowadays we cannot conceive modern operations without maps and geo-spatial information (GI). Information and knowledge management is fundamental to the success of organizational decisions in an uncertainty environment. The georeferenced information management is a process of knowledge management, it begins in the raw data and ends on generating knowledge. GI and intelligence systems allow us to integrate all other forms of intelligence and can be a main platform to process and display geo-spatial-time referenced events. Combining explicit knowledge with peoples know-how to generate a continuous learning cycle that supports real time decisions mitigates the influences of fog of everyday competition and provides the knowledge supremacy. Extending the preliminary analysis done in [1], this work applies the exploratory factor analysis to a questionnaire about the GI and intelligence management in an organization company allowing to identify future lines of action to improve information process sharing and exploration of all the potential of this important resource.

Connecting Multiple Intelligences through Open and Distance Learning: Going towards a Collective Intelligence?

ERIC Educational Resources Information Center

Medeiros Vieira, Leandro Mauricio; Ferasso, Marcos; Schröeder, Christine da Silva

2014-01-01

This theoretical essay is a learning approach reflexion on Howard Gardner's Theory of Multiple Intelligences and the possibilities provided by the education model known as open and distance learning. Open and distance learning can revolutionize traditional pedagogical practice, meeting the needs of those who have different forms of cognitive…

Collaborative Learning: Group Interaction in an Intelligent Mobile-Assisted Multiple Language Learning System

ERIC Educational Resources Information Center

Troussas, Christos; Virvou, Maria; Alepis, Efthimios

2014-01-01

This paper proposes a student-oriented approach tailored to effective collaboration between students using mobile phones for language learning within the life cycle of an intelligent tutoring system. For this reason, in this research, a prototype mobile application has been developed for multiple language learning that incorporates intelligence in…

Addressing Diverse Learner Preferences and Intelligences with Emerging Technologies: Matching Models to Online Opportunities

ERIC Educational Resources Information Center

Zhang, Ke; Bonk, Curtis J.

2008-01-01

This paper critically reviews various learning preferences and human intelligence theories and models with a particular focus on the implications for online learning. It highlights a few key models, Gardner's multiple intelligences, Fleming and Mills' VARK model, Honey and Mumford's Learning Styles, and Kolb's Experiential Learning Model, and…

Models of Learning in ICAI.

ERIC Educational Resources Information Center

Duchastel, P.; And Others

1989-01-01

Discusses intelligent computer assisted instruction (ICAI) and presents various models of learning which have been proposed. Topics discussed include artificial intelligence; intelligent tutorial systems; tutorial strategies; learner control; system design; learning theory; and knowledge representation of proper and improper (i.e., incorrect)…

Student's Uncertainty Modeling through a Multimodal Sensor-Based Approach

ERIC Educational Resources Information Center

Jraidi, Imene; Frasson, Claude

2013-01-01

Detecting the student internal state during learning is a key construct in educational environment and particularly in Intelligent Tutoring Systems (ITS). Students' uncertainty is of primary interest as it is deeply rooted in the process of knowledge construction. In this paper we propose a new sensor-based multimodal approach to model…

Intelligent Performance Assessment of Students' Laboratory Work in a Virtual Electronic Laboratory Environment

ERIC Educational Resources Information Center

Achumba, I. E.; Azzi, D.; Dunn, V. L.; Chukwudebe, G. A.

2013-01-01

Laboratory work is critical in undergraduate engineering courses. It is used to integrate theory and practice. This demands that laboratory activities are synchronized with lectures to maximize their derivable learning outcomes, which are measurable through assessment. The typical high costs of the traditional engineering laboratory, which often…

Optimists' Creed: Brave New Cyberlearning, Evolving Utopias (Circa 2041)

ERIC Educational Resources Information Center

Burleson, Winslow; Lewis, Armanda

2016-01-01

This essay imagines the role that artificial intelligence innovations play in the integrated living, learning and research environments of 2041. Here, in 2041, in the context of increasingly complex wicked challenges, whose solutions by their very nature continue to evade even the most capable experts, society and technology have co-evolved to…

Tutoring electronic troubleshooting in a simulated maintenance work environment

NASA Technical Reports Server (NTRS)

Gott, Sherrie P.

1987-01-01

A series of intelligent tutoring systems, or intelligent maintenance simulators, is being developed based on expert and novice problem solving data. A graded series of authentic troubleshooting problems provides the curriculum, and adaptive instructional treatments foster active learning in trainees who engage in extensive fault isolation practice and thus in conditionalizing what they know. A proof of concept training study involving human tutoring was conducted as a precursor to the computer tutors to assess this integrated, problem based approach to task analysis and instruction. Statistically significant improvements in apprentice technicians' troubleshooting efficiency were achieved after approximately six hours of training.

ISTAR: Intelligent System for Telemetry Analysis in Real-time

NASA Technical Reports Server (NTRS)

Simmons, Charles

1994-01-01

The intelligent system for telemetry analysis in real-time (ISTAR) is an advanced vehicle monitoring environment incorporating expert systems, analysis tools, and on-line hypermedia documentation. The system was developed for the Air Force Space and Missile Systems Center (SMC) in Los Angeles, California, in support of the inertial upper stage (IUS) booster vehicle. Over a five year period the system progressed from rapid prototype to operational system. ISTAR has been used to support five IUS missions and countless mission simulations. There were a significant number of lessons learned with respect to integrating an expert system capability into an existing ground system.

SKOPE-IT (Shareable Knowledge Objects as Portable Intelligent Tutors): Overlaying Natural Language Tutoring on an Adaptive Learning System for Mathematics

ERIC Educational Resources Information Center

Nye, Benjamin D.; Pavlik, Philip I., Jr.; Windsor, Alistair; Olney, Andrew M.; Hajeer, Mustafa; Hu, Xiangen

2018-01-01

Background: This study investigated learning outcomes and user perceptions from interactions with a hybrid intelligent tutoring system created by combining the AutoTutor conversational tutoring system with the Assessment and Learning in Knowledge Spaces (ALEKS) adaptive learning system for mathematics. This hybrid intelligent tutoring system (ITS)…

Emotional Intelligence among Auditory, Reading, and Kinesthetic Learning Styles of Elementary School Students in Ambon-Indonesia

ERIC Educational Resources Information Center

Leasa, Marleny; Corebima, Aloysius D.; Ibrohim; Suwono, Hadi

2017-01-01

Students have unique ways in managing the information in their learning process. VARK learning styles associated with memory are considered to have an effect on emotional intelligence. This quasi-experimental research was conducted to compare the emotional intelligence among the students having auditory, reading, and kinesthetic learning styles in…

Social learning and evolution: the cultural intelligence hypothesis

PubMed Central

van Schaik, Carel P.; Burkart, Judith M.

2011-01-01

If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer. PMID:21357223

Social learning and evolution: the cultural intelligence hypothesis.

PubMed

van Schaik, Carel P; Burkart, Judith M

2011-04-12

If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer.

Emotional Intelligence Profiles and Learning Strategies in Secondary School Students

ERIC Educational Resources Information Center

Inglés, Cándido J.; Martínez-Monteagudo, María C.; Pérez Fuentes, Maria C.; García-Fernández, José M.; Molero, María del Mar; Suriá-Martinez, Raquel; Gázquez, José J.

2017-01-01

The aim of this study was to analyse the relationship among emotional intelligence (EI) and learning strategies, identifying different emotional intelligence profiles and determining possible statistically significant differences in learning strategies through the identified profiles. Thousand and seventy-one Spaniards secondary school students…

The Artificial Intelligence Applications to Learning Programme.

ERIC Educational Resources Information Center

Williams, Noel

1992-01-01

Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…

The Nature of Intelligence and Its Relation to Learning.

ERIC Educational Resources Information Center

Jensen, Arthur R.

1979-01-01

The author presents intelligence and learning as theoretically and empirically separate concepts. Examining Spearman's "g" factor and the evolution, phylogeny and psychometrics of intelligence, he concludes that "g" is of dominant importance in scholastic learning. He notes some implications for equal educational opportunity.…

Developing a reading concentration monitoring system by applying an artificial bee colony algorithm to e-books in an intelligent classroom.

PubMed

Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

2012-10-22

A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students.

Developing a Reading Concentration Monitoring System by Applying an Artificial Bee Colony Algorithm to E-Books in an Intelligent Classroom

PubMed Central

Hsu, Chia-Cheng; Chen, Hsin-Chin; Su, Yen-Ning; Huang, Kuo-Kuang; Huang, Yueh-Min

2012-01-01

A growing number of educational studies apply sensors to improve student learning in real classroom settings. However, how can sensors be integrated into classrooms to help instructors find out students' reading concentration rates and thus better increase learning effectiveness? The aim of the current study was to develop a reading concentration monitoring system for use with e-books in an intelligent classroom and to help instructors find out the students' reading concentration rates. The proposed system uses three types of sensor technologies, namely a webcam, heartbeat sensor, and blood oxygen sensor to detect the learning behaviors of students by capturing various physiological signals. An artificial bee colony (ABC) optimization approach is applied to the data gathered from these sensors to help instructors understand their students' reading concentration rates in a classroom learning environment. The results show that the use of the ABC algorithm in the proposed system can effectively obtain near-optimal solutions. The system has a user-friendly graphical interface, making it easy for instructors to clearly understand the reading status of their students. PMID:23202042

Intelligent path loss prediction engine design using machine learning in the urban outdoor environment

NASA Astrophysics Data System (ADS)

Wang, Ruichen; Lu, Jingyang; Xu, Yiran; Shen, Dan; Chen, Genshe; Pham, Khanh; Blasch, Erik

2018-05-01

Due to the progressive expansion of public mobile networks and the dramatic growth of the number of wireless users in recent years, researchers are motivated to study the radio propagation in urban environments and develop reliable and fast path loss prediction models. During last decades, different types of propagation models are developed for urban scenario path loss predictions such as the Hata model and the COST 231 model. In this paper, the path loss prediction model is thoroughly investigated using machine learning approaches. Different non-linear feature selection methods are deployed and investigated to reduce the computational complexity. The simulation results are provided to demonstratethe validity of the machine learning based path loss prediction engine, which can correctly determine the signal propagation in a wireless urban setting.

From machine learning to deep learning: progress in machine intelligence for rational drug discovery.

PubMed

Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao

2017-11-01

Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.

Facilitating Multiple Intelligences through Multimodal Learning Analytics

ERIC Educational Resources Information Center

Perveen, Ayesha

2018-01-01

This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner's 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as…

The Intelligent Method of Learning

ERIC Educational Resources Information Center

Moula, Alireza; Mohseni, Simin; Starrin, Bengt; Scherp, Hans Ake; Puddephatt, Antony J.

2010-01-01

Early psychologist William James [1842-1910] and philosopher John Dewey [1859-1952] described intelligence as a method which can be learned. That view of education is integrated with knowledge about the brain's executive functions to empower pupils to intelligently organize their learning. This article links the pragmatist philosophy of…

LIA: An Intelligent Advisor for E-Learning

ERIC Educational Resources Information Center

Capuano, Nicola; Gaeta, Matteo; Marengo, Agostino; Miranda, Sergio; Orciuoli, Francesco; Ritrovato, Pierluigi

2009-01-01

Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA)…

Adaptive Critic Nonlinear Robust Control: A Survey.

PubMed

Wang, Ding; He, Haibo; Liu, Derong

2017-10-01

Adaptive dynamic programming (ADP) and reinforcement learning are quite relevant to each other when performing intelligent optimization. They are both regarded as promising methods involving important components of evaluation and improvement, at the background of information technology, such as artificial intelligence, big data, and deep learning. Although great progresses have been achieved and surveyed when addressing nonlinear optimal control problems, the research on robustness of ADP-based control strategies under uncertain environment has not been fully summarized. Hence, this survey reviews the recent main results of adaptive-critic-based robust control design of continuous-time nonlinear systems. The ADP-based nonlinear optimal regulation is reviewed, followed by robust stabilization of nonlinear systems with matched uncertainties, guaranteed cost control design of unmatched plants, and decentralized stabilization of interconnected systems. Additionally, further comprehensive discussions are presented, including event-based robust control design, improvement of the critic learning rule, nonlinear H ∞ control design, and several notes on future perspectives. By applying the ADP-based optimal and robust control methods to a practical power system and an overhead crane plant, two typical examples are provided to verify the effectiveness of theoretical results. Overall, this survey is beneficial to promote the development of adaptive critic control methods with robustness guarantee and the construction of higher level intelligent systems.

Toward interactive context-aware affective educational recommendations in computer-assisted language learning

NASA Astrophysics Data System (ADS)

Santos, Olga C.; Saneiro, Mar; Boticario, Jesus G.; Rodriguez-Sanchez, M. C.

2016-01-01

This work explores the benefits of supporting learners affectively in a context-aware learning situation. This features a new challenge in related literature in terms of providing affective educational recommendations that take advantage of ambient intelligence and are delivered through actuators available in the environment, thus going beyond previous approaches which provided computer-based recommendation that present some text or tell aloud the learner what to do. To address this open issue, we have applied TORMES elicitation methodology, which has been used to investigate the potential of ambient intelligence for making more interactive recommendations in an emotionally challenging scenario (i.e. preparing for the oral examination of a second language learning course). Arduino open source electronics prototyping platform is used both to sense changes in the learners' affective state and to deliver the recommendation in a more interactive way through different complementary sensory communication channels (sight, hearing, touch) to cope with a universal design. An Ambient Intelligence Context-aware Affective Recommender Platform (AICARP) has been built to support the whole experience, which represents a progress in the state of the art. In particular, we have come up with what is most likely the first interactive context-aware affective educational recommendation. The value of this contribution lies in discussing methodological and practical issues involved.

Personalized E- learning System Based on Intelligent Agent

NASA Astrophysics Data System (ADS)

Duo, Sun; Ying, Zhou Cai

Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.

Utilization of Intelligent Software Agent Features for Improving E-Learning Efforts: A Comprehensive Investigation

ERIC Educational Resources Information Center

Farzaneh, Mandana; Vanani, Iman Raeesi; Sohrabi, Babak

2012-01-01

E-learning is one of the most important learning approaches within which intelligent software agents can be efficiently used so as to automate and facilitate the process of learning. The aim of this paper is to illustrate a comprehensive categorization of intelligent software agent features, which is valuable for being deployed in the virtual…

Comparison of learning models based on mathematics logical intelligence in affective domain

NASA Astrophysics Data System (ADS)

Widayanto, Arif; Pratiwi, Hasih; Mardiyana

2018-04-01

The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

The Strategic Partners Network's Extraction: The XStrat.Net Project

NASA Astrophysics Data System (ADS)

Taifi, Nouha; Passiante, Giuseppina

The firms in the business environment have to choose adequate partners in order to sustain their competitive advantage and their economic performance. Plus, the creation of special communities consisting of these partners is essential for the life-long development of these latter and the firms creating them. The research project XStrat.Net aims at the identification of factors and indicators about the organizations for the modelling of intelligent agents -XStrat intelligent agents- and the engineering of a software -XStrat- to process these backbones intelligent agents. Through the use of the software, the firms will be able to select the needed partners for the creation of special communities for the purpose of learning, interest or innovation. The XStrat.Net project also intends to provide guidelines for the creation of the special communities.

Improving fluid intelligence with training on working memory.

PubMed

Jaeggi, Susanne M; Buschkuehl, Martin; Jonides, John; Perrig, Walter J

2008-05-13

Fluid intelligence (Gf) refers to the ability to reason and to solve new problems independently of previously acquired knowledge. Gf is critical for a wide variety of cognitive tasks, and it is considered one of the most important factors in learning. Moreover, Gf is closely related to professional and educational success, especially in complex and demanding environments. Although performance on tests of Gf can be improved through direct practice on the tests themselves, there is no evidence that training on any other regimen yields increased Gf in adults. Furthermore, there is a long history of research into cognitive training showing that, although performance on trained tasks can increase dramatically, transfer of this learning to other tasks remains poor. Here, we present evidence for transfer from training on a demanding working memory task to measures of Gf. This transfer results even though the trained task is entirely different from the intelligence test itself. Furthermore, we demonstrate that the extent of gain in intelligence critically depends on the amount of training: the more training, the more improvement in Gf. That is, the training effect is dosage-dependent. Thus, in contrast to many previous studies, we conclude that it is possible to improve Gf without practicing the testing tasks themselves, opening a wide range of applications.

Improving fluid intelligence with training on working memory

PubMed Central

Jaeggi, Susanne M.; Buschkuehl, Martin; Jonides, John; Perrig, Walter J.

2008-01-01

Fluid intelligence (Gf) refers to the ability to reason and to solve new problems independently of previously acquired knowledge. Gf is critical for a wide variety of cognitive tasks, and it is considered one of the most important factors in learning. Moreover, Gf is closely related to professional and educational success, especially in complex and demanding environments. Although performance on tests of Gf can be improved through direct practice on the tests themselves, there is no evidence that training on any other regimen yields increased Gf in adults. Furthermore, there is a long history of research into cognitive training showing that, although performance on trained tasks can increase dramatically, transfer of this learning to other tasks remains poor. Here, we present evidence for transfer from training on a demanding working memory task to measures of Gf. This transfer results even though the trained task is entirely different from the intelligence test itself. Furthermore, we demonstrate that the extent of gain in intelligence critically depends on the amount of training: the more training, the more improvement in Gf. That is, the training effect is dosage-dependent. Thus, in contrast to many previous studies, we conclude that it is possible to improve Gf without practicing the testing tasks themselves, opening a wide range of applications. PMID:18443283

Intelligent Image Based Computer Aided Education (IICAE)

NASA Astrophysics Data System (ADS)

David, Amos A.; Thiery, Odile; Crehange, Marion

1989-03-01

Artificial Intelligence (AI) has found its way into Computer Aided Education (CAE), and there are several systems constructed to put in evidence its interesting advantages. We believe that images (graphic or real) play an important role in learning. However, the use of images, outside their use as illustration, makes it necessary to have applications such as AI. We shall develop the application of AI in an image based CAE and briefly present the system under construction to put in evidence our concept. We shall also elaborate a methodology for constructing such a system. Futhermore we shall briefly present the pedagogical and psychological activities in a learning process. Under the pedagogical and psychological aspect of learning, we shall develop areas such as the importance of image in learning both as pedagogical objects as well as means for obtaining psychological information about the learner. We shall develop the learner's model, its use, what to build into it and how. Under the application of AI in an image based CAE, we shall develop the importance of AI in exploiting the knowledge base in the learning environment and its application as a means of implementing pedagogical strategies.

Multiple Intelligences, Motivations and Learning Experience Regarding Video-Assisted Subjects in a Rural University

ERIC Educational Resources Information Center

Hajhashemi, Karim; Caltabiano, Nerina; Anderson, Neil; Tabibzadeh, Seyed Asadollah

2018-01-01

This study investigates multiple intelligences in relation to online video experiences, age, gender, and mode of learning from a rural Australian university. The inter-relationships between learners' different intelligences and their motivations and learning experience with the supplementary online videos utilised in their subjects are…

IS Learning: The Impact of Gender and Team Emotional Intelligence

ERIC Educational Resources Information Center

Dunaway, Mary M.

2013-01-01

In university settings, dysfunction in teamwork often challenges problem-based learning in IS projects. Researchers of IS Education have largely overlooked Team Emotional Intelligence (TEI), which offers a collective cognitive skill that may benefit the student learning experience. Hypothesized are four dimensions of emotional intelligence (EI)…

Intelligence moderates reinforcement learning: a mini-review of the neural evidence

PubMed Central

2014-01-01

Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. PMID:25185818

Intelligence moderates reinforcement learning: a mini-review of the neural evidence.

PubMed

Chen, Chong

2015-06-01

Our understanding of the neural basis of reinforcement learning and intelligence, two key factors contributing to human strivings, has progressed significantly recently. However, the overlap of these two lines of research, namely, how intelligence affects neural responses during reinforcement learning, remains uninvestigated. A mini-review of three existing studies suggests that higher IQ (especially fluid IQ) may enhance the neural signal of positive prediction error in dorsolateral prefrontal cortex, dorsal anterior cingulate cortex, and striatum, several brain substrates of reinforcement learning or intelligence. Copyright © 2015 the American Physiological Society.

The Prediction of Students' Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning.

PubMed

Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen

2015-01-01

The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.

The Prediction of Students’ Academic Performance With Fluid Intelligence in Giving Special Consideration to the Contribution of Learning

PubMed Central

Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen

2015-01-01

The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school. PMID:26435760

Pathways of Learning: Teaching Students and Parents about Multiple Intelligences.

ERIC Educational Resources Information Center

Lazear, David

This book is concerned with reinventing the learning process from a multiple intelligences perspective and urges explicitly teaching students about multiple intelligences to further their metacognitive understanding. The multiple-intelligence-based curriculum is intended to interface with the regular academic curriculum. An introductory chapter…

Learning in and from brain-based devices.

PubMed

Edelman, Gerald M

2007-11-16

Biologically based mobile devices have been constructed that differ from robots based on artificial intelligence. These brain-based devices (BBDs) contain simulated brains that autonomously categorize signals from the environment without a priori instruction. Two such BBDs, Darwin VII and Darwin X, are described here. Darwin VII recognizes objects and links categories to behavior through instrumental conditioning. Darwin X puts together the "what,"when," and "where" from cues in the environment into an episodic memory that allows it to find a desired target. Although these BBDs are designed to provide insights into how the brain works, their principles may find uses in building hybrid machines. These machines would combine the learning ability of BBDs with explicitly programmed control systems.

Market Model for Resource Allocation in Emerging Sensor Networks with Reinforcement Learning

PubMed Central

Zhang, Yue; Song, Bin; Zhang, Ying; Du, Xiaojiang; Guizani, Mohsen

2016-01-01

Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management. PMID:27916841

Self-Study in Emotion Work: Organizing Chaos by Negotiating Private and Public Grief

ERIC Educational Resources Information Center

Farnsworth, Megan

2016-01-01

In order to improve her practice, a teacher educator explored emotions as catalysts for teaching and learning by asking the research question, "How can I support preservice teachers' emotional intelligence (EI), as well as my own, as we negotiate the impact of strong emotions in the pedagogical environment?" Three levels of reflection…

Providing Graduated Corrective Feedback in an Intelligent Computer-Assisted Language Learning Environment

ERIC Educational Resources Information Center

Ai, Haiyang

2017-01-01

Corrective feedback (CF), a response to linguistic errors made by second language (L2) learners, has received extensive scholarly attention in second language acquisition. While much of the previous research in the field has focused on whether CF facilitates or impedes L2 development, few studies have examined the efficacy of gradually modifying…

Supporting Collaborative Learning and Problem-Solving in a Constraint-Based CSCL Environment for UML Class Diagrams

ERIC Educational Resources Information Center

Baghaei, Nilufar; Mitrovic, Antonija; Irwin, Warwick

2007-01-01

We present COLLECT-UML, a constraint-based intelligent tutoring system (ITS) that teaches object-oriented analysis and design using Unified Modelling Language (UML). UML is easily the most popular object-oriented modelling technology in current practice. While teaching how to design UML class diagrams, COLLECT-UML also provides feedback on…

Business Intelligence Basics: Multi-Modal Means of Analyzing Data Can Produce Actionable Results

ERIC Educational Resources Information Center

Mills, Lane

2008-01-01

School systems face many decisions in developing and maintaining learning environments that create success for all students. From district operations to the classroom, district leaders implement solutions and take action based on the information they have at hand. While there is no shortage of data, turning that data into useful information is as…

The Relationship between Emotional Intelligence and Productive Language Skills

ERIC Educational Resources Information Center

Genç, Gülten; Kulusakh, Emine; Aydin, Savas

2016-01-01

Emotional intelligence has recently attracted educators' attention around the world. Educators who try to investigate the factors in language learning achievement have decided to pave the way to success through emotional intelligence. The relationship between emotional intelligence and language learning is the major concern of this study. The…

The Representation of Motor (Inter)action, States of Action, and Learning: Three Perspectives on Motor Learning by Way of Imagery and Execution

PubMed Central

Frank, Cornelia; Schack, Thomas

2017-01-01

Learning in intelligent systems is a result of direct and indirect interaction with the environment. While humans can learn by way of different states of (inter)action such as the execution or the imagery of an action, their unique potential to induce brain- and mind-related changes in the motor action system is still being debated. The systematic repetition of different states of action (e.g., physical and/or mental practice) and their contribution to the learning of complex motor actions has traditionally been approached by way of performance improvements. More recently, approaches highlighting the role of action representation in the learning of complex motor actions have evolved and may provide additional insight into the learning process. In the present perspective paper, we build on brain-related findings and sketch recent research on learning by way of imagery and execution from a hierarchical, perceptual-cognitive approach to motor control and learning. These findings provide insights into the learning of intelligent systems from a perceptual-cognitive, representation-based perspective and as such add to our current understanding of action representation in memory and its changes with practice. Future research should build bridges between approaches in order to more thoroughly understand functional changes throughout the learning process and to facilitate motor learning, which may have particular importance for cognitive systems research in robotics, rehabilitation, and sports. PMID:28588510

The specificity of parenting effects: Differential relations of parent praise and criticism to children's theories of intelligence and learning goals.

PubMed

Gunderson, Elizabeth A; Donnellan, M Brent; Robins, Richard W; Trzesniewski, Kali H

2018-04-24

Individuals who believe that intelligence can be improved with effort (an incremental theory of intelligence) and who approach challenges with the goal of improving their understanding (a learning goal) tend to have higher academic achievement. Furthermore, parent praise is associated with children's incremental theories and learning goals. However, the influences of parental criticism, as well as different forms of praise and criticism (e.g., process vs. person), have received less attention. We examine these associations by analyzing two existing datasets (Study 1: N = 317 first to eighth graders; Study 2: N = 282 fifth and eighth graders). In both studies, older children held more incremental theories of intelligence, but lower learning goals, than younger children. Unexpectedly, the relation between theories of intelligence and learning goals was nonsignificant and did not vary with children's grade level. In both studies, overall perceived parent praise positively related to children's learning goals, whereas perceived parent criticism negatively related to incremental theories of intelligence. In Study 2, perceived parent process praise was the only significant (positive) predictor of children's learning goals, whereas perceived parent person criticism was the only significant (negative) predictor of incremental theories of intelligence. Finally, Study 2 provided some support for our hypothesis that age-related differences in perceived parent praise and criticism can explain age-related differences in children's learning goals. Results suggest that incremental theories of intelligence and learning goals might not be strongly related during childhood and that perceived parent praise and criticism have important, but distinct, relations with each motivational construct. Copyright © 2018 Elsevier Inc. All rights reserved.

Maze learning by a hybrid brain-computer system

NASA Astrophysics Data System (ADS)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system.

PubMed

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-13

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system

PubMed Central

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-01-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation. PMID:27619326

The effect of multiple intelligence-based learning towards students’ concept mastery and interest in learning matter

NASA Astrophysics Data System (ADS)

Pratiwi, W. N.; Rochintaniawati, D.; Agustin, R. R.

2018-05-01

This research was focused on investigating the effect of multiple intelligence -based learning as a learning approach towards students’ concept mastery and interest in learning matter. The one-group pre-test - post-test design was used in this research towards a sample which was according to the suitable situation of the research sample, n = 13 students of the 7th grade in a private school in Bandar Seri Begawan. The students’ concept mastery was measured using achievement test and given at the pre-test and post-test, meanwhile the students’ interest level was measured using a Likert Scale for interest. Based on the analysis of the data, the result shows that the normalized gain was .61, which was considered as a medium improvement. in other words, students’ concept mastery in matter increased after being taught using multiple intelligence-based learning. The Likert scale of interest shows that most students have a high interest in learning matter after being taught by multiple intelligence-based learning. Therefore, it is concluded that multiple intelligence – based learning helped in improving students’ concept mastery and gain students’ interest in learning matter.

A junction-tree based learning algorithm to optimize network wide traffic control: A coordinated multi-agent framework

DOE PAGES

Zhu, Feng; Aziz, H. M. Abdul; Qian, Xinwu; ...

2015-01-31

Our study develops a novel reinforcement learning algorithm for the challenging coordinated signal control problem. Traffic signals are modeled as intelligent agents interacting with the stochastic traffic environment. The model is built on the framework of coordinated reinforcement learning. The Junction Tree Algorithm (JTA) based reinforcement learning is proposed to obtain an exact inference of the best joint actions for all the coordinated intersections. Moreover, the algorithm is implemented and tested with a network containing 18 signalized intersections in VISSIM. Finally, our results show that the JTA based algorithm outperforms independent learning (Q-learning), real-time adaptive learning, and fixed timing plansmore » in terms of average delay, number of stops, and vehicular emissions at the network level.« less

The TENOR Architecture for Advanced Distributed Learning and Intelligent Training

DTIC Science & Technology

2002-01-01

called TENOR, for Training Education Network on Request. There have been a number of recent learning systems developed that leverage off Internet...AG2-14256 AIAA 2002-1054 The TENOR Architecture for Advanced Distributed Learning and Intelligent Training C. Tibaudo, J. Kristl and J. Schroeder...COVERED 4. TITLE AND SUBTITLE The TENOR Architecture for Advanced Distributed Learning and Intelligent Training 5a. CONTRACT NUMBER F33615-00-M

EFL Learners' Self-Perceived Strategy Use across Various Intelligence Types: A Case Study

ERIC Educational Resources Information Center

Tahriri, Abdorreza; Divsar, Hoda

2011-01-01

Increasing attention paid to learner-centered pedagogy in recent years has highlighted the examination of intelligence and language learning strategies (LLSs) among others. This study explores EFL learners' perceived use of language learning strategies across various intelligence types as reflected in Gardner's 1983 Multiple Intelligences Theory.…

AVID Students' Perceptions of Intelligence: A Mixed Methods Study

ERIC Educational Resources Information Center

Becker, John Darrell

2012-01-01

Students' perceptions of intelligence have been shown to have an effect on learning. Students who see intelligence as something that can be developed, those with a growth mindset, often experience academic success, while those who perceive intelligence to be a fixed entity are typically less likely to take on challenging learning experiences and…

Individual differences: Case studies of rodent and primate intelligence.

PubMed

Matzel, Louis D; Sauce, Bruno

2017-10-01

Early in the 20th century, individual differences were a central focus of psychologists. By the end of that century, studies of individual differences had become far less common, and attention to these differences played little role in the development of contemporary theory. To illustrate the important role of individual differences, here we consider variations in intelligence as a compelling example. General intelligence (g) has now been demonstrated in at least 2 distinct genera: primates (including humans, chimpanzees, bonobos, and tamarins) and rodents (mice and rats). The expression of general intelligence varies widely across individuals within a species; these variations have tremendous functional consequence, and are attributable to interactions of genes and environment. Here we provide evidence for these assertions, describe the processes that contribute to variations in general intelligence, as well as the methods that underlie the analysis of individual differences. We conclude by describing why consideration of individual differences is critical to our understanding of learning, cognition, and behavior, and illustrate how attention to individual differences can contribute to more effective administration of therapeutic strategies for psychological disorders. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Plant intelligence

PubMed Central

Lipavská, Helena; Žárský, Viktor

2009-01-01

The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Fikes, R. E.; Chaitin, L. J.; Hart, P. E.; Duda, R. O.; Nilsson, N. J.

1971-01-01

A program of research in the field of artificial intelligence is presented. The research areas discussed include automatic theorem proving, representations of real-world environments, problem-solving methods, the design of a programming system for problem-solving research, techniques for general scene analysis based upon television data, and the problems of assembling an integrated robot system. Major accomplishments include the development of a new problem-solving system that uses both formal logical inference and informal heuristic methods, the development of a method of automatic learning by generalization, and the design of the overall structure of a new complete robot system. Eight appendices to the report contain extensive technical details of the work described.

Theories of Intelligence, Learning, and Motivation as a Basic Educational Praxis

ERIC Educational Resources Information Center

Van Hook, Steven R.

2008-01-01

This article begins with an examination of the early building blocks of intelligence and learning through signs and symbols, such as examined by Vygotsky and Freire. Then the inquiry moves into methods of achieving resonance as praxis of learning as expanded on by Freire, and connecting with students by addressing their multiple intelligences as…

Problem-Based Learning Pedagogies: Psychological Processes and Enhancement of Intelligences

ERIC Educational Resources Information Center

Tan, Oon-Seng

2007-01-01

Education in this 21st century is concerned with developing intelligences. Problem solving in real-world contexts involves multiple ways of knowing and learning. Intelligence in the real world involves not only learning how to do things effectively but also more importantly the ability to deal with novelty and growing our capacity to adapt, select…

Complex learning: the role of knowledge, intelligence, motivation and learning strategies.

PubMed

Castejón, Juan L; Gilar, Raquel; Pérez, Antonio M

2006-11-01

This work presents the main theories and models formulated with the purpose of offering a global overview on the acquisition of knowledge and skills involved in the initial development of expert competence. Setting from this background, we developed an empirical work whose main purpose is to define those factors in a complex learning situation such as chapter-sized in a knowledge-rich domain. The results obtained in a sample of Master students reveal that the several variables intervening, such as the qualitative organization of knowledge, intellectual ability, motivation, the deliberate use of strategies, and a rich learning environment, contribute in an independent way to provide an explanation for the acquired knowledge.

Thutmose - Investigation of Machine Learning-Based Intrusion Detection Systems

DTIC Science & Technology

2016-06-01

research is being done to incorporate the field of machine learning into intrusion detection. Machine learning is a branch of artificial intelligence (AI...adversarial drift." Proceedings of the 2013 ACM workshop on Artificial intelligence and security. ACM. (2013) Kantarcioglu, M., Xi, B., and Clifton, C. "A...34 Proceedings of the 4th ACM workshop on Security and artificial intelligence . ACM. (2011) Dua, S., and Du, X. Data Mining and Machine Learning in

Suitable Learning Styles for Intelligent Tutoring Technologies (Styles d’Apprentissage Appropries pour les Technologies Tuteurs Intelligents)

DTIC Science & Technology

2010-05-01

mind, (ii) forms of mental self-government, and (iii) stylistic preferences. Importantly, Sternberg does not think that cognitive style...summarizes a study examining suitable cognitive and learning styles for intelligent tutoring technologies to improve the Canadian Forces (CF) distance...are the appropriate tool to address CF learning needs, as e-learning systems: • Cater to all individuals in the CF regardless of their cognitive or

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

In the Context of Multiple Intelligences Theory, Intelligent Data Analysis of Learning Styles Was Based on Rough Set Theory

ERIC Educational Resources Information Center

Narli, Serkan; Ozgen, Kemal; Alkan, Huseyin

2011-01-01

The present study aims to identify the relationship between individuals' multiple intelligence areas and their learning styles with mathematical clarity using the concept of rough sets which is used in areas such as artificial intelligence, data reduction, discovery of dependencies, prediction of data significance, and generating decision…

Contribution to Language Teaching and Learning: A Review of Emotional Intelligence

ERIC Educational Resources Information Center

Sucaromana, Usaporn

2012-01-01

The aim of this paper is to introduce the importance of emotional intelligence and the extent to which emotional intelligence can be implemented and used to improve language teaching and learning. Since emotional intelligence is perceived to play a crucial part in every aspect of people's lives, it can be extended to language teaching and…

Commentary on: "Toward Computer-Based Support of Metacognitive Skills: A Computational Framework to Coach Self Explanation"

ERIC Educational Resources Information Center

Conati, Cristina

2016-01-01

This paper is a commentary on "Toward Computer-Based Support of Meta-Cognitive Skills: a Computational Framework to Coach Self-Explanation", by Cristina Conati and Kurt Vanlehn, published in the "IJAED" in 2000 (Conati and VanLehn 2010). This work was one of the first examples of Intelligent Learning Environments (ILE) that…

Mentoring Student Teachers Into The Profession: Intentionally Creating a Culture of Inquiry in the Context of Media and Technology Practice

ERIC Educational Resources Information Center

Jacobsen, Michele; Friesen, Sharon; Clifford, Pat

2004-01-01

What is the nature of onsite and online mentoring which enables student teachers to design inquiry-based, technology rich learning experiences? In this case study, faculty and expert teachers worked with fifteen student teachers during an elementary school practicum. An online intelligent design environment supported the development of a community…

Framework for Intelligent Teaching and Training Systems -- A Study of Systems

ERIC Educational Resources Information Center

Graf von Malotky, Nikolaj Troels; Martens, Alke

2016-01-01

Intelligent Tutoring System are state of the art in eLearning since the late 1980s. The earliest system have been developed in teams of psychologists and computer scientists, with the goal to investigate learning processes and, later on with the goal to intelligently support teaching and training with computers. Over the years, the eLearning hype…

The relationship between learning styles, emotional social intelligence, and academic success of undergraduate nursing students.

PubMed

Suliman, Wafika A

2010-06-01

Feelings or emotions and thinking have been identified as forces that may affect one's learning styles (D. A. Kolb, 1984), emotional social intelligence, and success (R. Bar-On, 2004). This study on the relationship between academic success and the two variables of learning abilities or styles and emotional social intelligence was conducted at two colleges of nursing in Saudi Arabia. Both offer conventional and accelerated undergraduate nursing education programs. This study was designed to explore the preferred learning abilities or styles of Saudi nursing students in conventional and accelerated programs, the difference in emotional social intelligence between the two, and the relationships between academic success and learning styles and emotional social intelligence. A convenience sample was recruited, consisting of a total of 98 students, 50 and 48 of whom were enrolled, respectively, in conventional and accelerated programs. Self-administered instruments including the Kolb learning style inventory and the Bar-On emotional quotient inventory (EQ-i) were used to collect data, which were analyzed quantitatively. Both groups were found to favor a diverger style of learning, with total EQ-i scores showing no statistical difference between the two (t = 1.251, p =.214). "Self-regard" and "problem solving" earned the highest EQ-i content subscale scores for both groups. Pearson's correlation coefficient showed no significant relationship between learning abilities or styles and emotional social intelligence and academic success. The findings suggest that either no actual relationship exists or that emotional social intelligence may be confounded with factors such as professional and cultural values.

Development of an evolutionary simulator and an overall control system for intelligent wheelchair

NASA Astrophysics Data System (ADS)

Imai, Makoto; Kawato, Koji; Hamagami, Tomoki; Hirata, Hironori

The goal of this research is to develop an intelligent wheelchair (IWC) system which aids an indoor safe mobility for elderly and disabled people with a new conceptual architecture which realizes autonomy, cooperativeness, and a collaboration behavior. In order to develop the IWC system in real environment, we need design-tools and flexible architecture. In particular, as more significant ones, this paper describes two key techniques which are an evolutionary simulation and an overall control mechanism. The evolutionary simulation technique corrects the error between the virtual environment in a simulator and real one in during the learning of an IWC agent, and coevolves with the agent. The overall control mechanism is implemented with subsumption architecture which is employed in an autonomous robot controller. By using these techniques in both simulations and experiments, we confirm that our IWC system acquires autonomy, cooperativeness, and a collaboration behavior efficiently.

An Intelligent System for Determining Learning Style

ERIC Educational Resources Information Center

Ozdemir, Ali; Alaybeyoglu, Aysegul; Mulayim, Naciye; Uysal, Muhammed

2018-01-01

In this study, an intelligent system which determines learning style of the students is developed to increase success in effective and easy learning. The importance of the proposed software system is to determine convenience degree of the student's learning style. Personal information form and Dunn Learning Style Preference Survey are used to…

Multiple Intelligences for Differentiated Learning

ERIC Educational Resources Information Center

Williams, R. Bruce

2007-01-01

There is an intricate literacy to Gardner's multiple intelligences theory that unlocks key entry points for differentiated learning. Using a well-articulated framework, rich with graphic representations, Williams provides a comprehensive discussion of multiple intelligences. He moves the teacher and students from curiosity, to confidence, to…

The effects of two EFL (English as a foreign language) teaching approaches studied by the cotwin control method: a comparative study of the communicative and the grammatical approaches.

PubMed

Ando, J

1992-01-01

The present study compared two different types of English-language teaching approaches, the grammatical approach (GA) and the communicative approach (CA), by the cotwin control method. This study has two purposes: to study the effects of teaching approaches and to estimate genetic influences upon learning aptitudes. Seven pairs of identical twins (MZ) and 4 pairs of fraternal twins (DZ) participated in the experiment along with 68 other nontwin fifth graders. Each cotwin was assigned to the GA and CA respectively and received 20 hours of lessons over a 10-day period. The behavioral similarities between MZ cotwins were statistically and descriptively depicted. No major effect of either teaching approach was noted, but the genetic influence upon individual differences of learning achievement was obvious. Furthermore, an interesting interaction between the teaching approaches and intelligence was found, that is, that the GA capitalises on and CA compensates for intelligence. This interactional pattern could be interpreted as an example of genotype-environment interaction. The relationship between genetic factors and learning aptitudes is discussed.

The relationship between emotional intelligence competencies and preferred conflict-handling styles.

PubMed

Morrison, Jeanne

2008-11-01

The purpose of this study was to determine if a relationship exists between emotional intelligence (EI) and preferred conflict-handling styles of registered nurses. Conflict cannot be eliminated from the workplace therefore learning appropriate conflict-handling skills is important. Ninety-four registered nurses working in three south Mississippi healthcare facilities participated in this quantitative study. Ninety-two valid sets of data instruments were collected for this study. Higher levels of EI positively correlated with collaborating and negatively with accommodating. The issue of occupational stress and conflict among nurses is a major concern. It is imperative nurses learn how to effectively handle conflict in the work environment. Developing the competencies of EI and understanding how to effectively handle conflict is necessary for nurses working in a highly stressful occupation. Effective leadership management includes conflict management and collaboration. The art of relationship management is necessary when handling other people's emotions. When conflict is approached with high levels of EI, it creates an opportunity for learning effective interpersonal skills. Understanding how EI levels and conflict skills correlate can be used to improve interpersonal relationships in a healthcare facility.

The relationship between epistemological beliefs, implicit theories of intelligence, and self-regulated learning among Norwegian postsecondary students.

PubMed

Bråten, Ivar; Strømsø, Helge I

2005-12-01

More empirical work is needed to examine the dimensionality of personal epistemology and relations between those dimensions and motivational and strategic components of self-regulated learning. In particular, there is great need to investigate personal epistemology and its relation to self-regulated learning across cultures and academic contexts. Because the demarcation between personal epistemology and implicit theories of intelligence has been questioned, dimensions of personal epistemology should also be studied in relation to implicit theories of intelligence. The primary aim was to examine the dimensionality of personal epistemology and the relation between those dimensions and implicit theories of intelligence in the cultural context of Norwegian postsecondary education. A secondary aim was to examine the relative contribution of epistemological beliefs and theories of intelligence to motivational and strategic components of self-regulated learning in different academic contexts within that culture. The first sample included 178 business administration students in a traditional transmission-oriented instructional context; the second, 108 student teachers in an innovative pedagogical context. The dimensionality of the Schommer Epistemological Questionnaire was examined through factor analyses, and the resulting dimensions were examined in relation to implicit theories of intelligence. We performed multiple regression analyses, separately for the two academic contexts, to try to predict motivational (i.e. self-efficacy beliefs, mastery goal orientation, and interest) and strategic (i.e. self-regulatory strategy use) components of self-regulated learning with epistemological beliefs and implicit theories of intelligence. Considerable cross-cultural generalizability was found for the dimensionality of personal epistemology. Moreover, the dimensions of personal epistemology seemed to represent constructs separate from the construct of implicit theories of intelligence. Differences in the predictability of the epistemological dimensions were found for the two samples. For the student teachers, belief about knowledge construction and modification was a better predictor of self-regulated learning. For the business administration students, belief about the certainty of knowledge played a more important role in self-regulated learning. Epistemological beliefs predict self-regulated learning among Norwegian postsecondary students and play more important roles than implicit theories of intelligence. Relations between epistemological beliefs and self-regulated learning may vary with academic context.

Distributed interactive virtual environments for collaborative experiential learning and training independent of distance over Internet2.

PubMed

Alverson, Dale C; Saiki, Stanley M; Jacobs, Joshua; Saland, Linda; Keep, Marcus F; Norenberg, Jeffrey; Baker, Rex; Nakatsu, Curtis; Kalishman, Summers; Lindberg, Marlene; Wax, Diane; Mowafi, Moad; Summers, Kenneth L; Holten, James R; Greenfield, John A; Aalseth, Edward; Nickles, David; Sherstyuk, Andrei; Haines, Karen; Caudell, Thomas P

2004-01-01

Medical knowledge and skills essential for tomorrow's healthcare professionals continue to change faster than ever before creating new demands in medical education. Project TOUCH (Telehealth Outreach for Unified Community Health) has been developing methods to enhance learning by coupling innovations in medical education with advanced technology in high performance computing and next generation Internet2 embedded in virtual reality environments (VRE), artificial intelligence and experiential active learning. Simulations have been used in education and training to allow learners to make mistakes safely in lieu of real-life situations, learn from those mistakes and ultimately improve performance by subsequent avoidance of those mistakes. Distributed virtual interactive environments are used over distance to enable learning and participation in dynamic, problem-based, clinical, artificial intelligence rules-based, virtual simulations. The virtual reality patient is programmed to dynamically change over time and respond to the manipulations by the learner. Participants are fully immersed within the VRE platform using a head-mounted display and tracker system. Navigation, locomotion and handling of objects are accomplished using a joy-wand. Distribution is managed via the Internet2 Access Grid using point-to-point or multi-casting connectivity through which the participants can interact. Medical students in Hawaii and New Mexico (NM) participated collaboratively in problem solving and managing of a simulated patient with a closed head injury in VRE; dividing tasks, handing off objects, and functioning as a team. Students stated that opportunities to make mistakes and repeat actions in the VRE were extremely helpful in learning specific principles. VRE created higher performance expectations and some anxiety among VRE users. VRE orientation was adequate but students needed time to adapt and practice in order to improve efficiency. This was also demonstrated successfully between Western Australia and UNM. We successfully demonstrated the ability to fully immerse participants in a distributed virtual environment independent of distance for collaborative team interaction in medical simulation designed for education and training. The ability to make mistakes in a safe environment is well received by students and has a positive impact on their understanding, as well as memory of the principles involved in correcting those mistakes. Bringing people together as virtual teams for interactive experiential learning and collaborative training, independent of distance, provides a platform for distributed "just-in-time" training, performance assessment and credentialing. Further validation is necessary to determine the potential value of the distributed VRE in knowledge transfer, improved future performance and should entail training participants to competence in using these tools.

Leading to Learning and Competitive Intelligence

ERIC Educational Resources Information Center

Luu, Trong Tuan

2013-01-01

Purpose: This research aims to examine whether there is the chain effect from corporate social responsibility (CSR) and emotional intelligence (EI) to organizational learning and competitive intelligence in chemical companies in a Vietnam business setting. Design/methodology/approach: Structural equation modeling (SEM) approach was used to analyze…

Little AI: Playing a constructivist robot

NASA Astrophysics Data System (ADS)

Georgeon, Olivier L.

Little AI is a pedagogical game aimed at presenting the founding concepts of constructivist learning and developmental Artificial Intelligence. It primarily targets students in computer science and cognitive science but it can also interest the general public curious about these topics. It requires no particular scientific background; even children can find it entertaining. Professors can use it as a pedagogical resource in class or in online courses. The player presses buttons to control a simulated "baby robot". The player cannot see the robot and its environment, and initially ignores the effects of the commands. The only information received by the player is feedback from the player's commands. The player must learn, at the same time, the functioning of the robot's body and the structure of the environment from patterns in the stream of commands and feedback. We argue that this situation is analogous to how infants engage in early-stage developmental learning (e.g., Piaget (1937), [1]).

In-Factory Learning - Qualification For The Factory Of The Future

NASA Astrophysics Data System (ADS)

Quint, Fabian; Mura, Katharina; Gorecky, Dominic

2015-07-01

The Industry 4.0 vision anticipates that internet technologies will find their way into future factories replacing traditional components by dynamic and intelligent cyber-physical systems (CPS) that combine the physical objects with their digital representation. Reducing the gap between the real and digital world makes the factory environment more flexible, more adaptive, but also more complex for the human workers. Future workers require interdisciplinary competencies from engineering, information technology, and computer science in order to understand and manage the diverse interrelations between physical objects and their digital counterpart. This paper proposes a mixed-reality based learning environment, which combines physical objects and visualisation of digital content via Augmented Reality. It uses reality-based interaction in order to make the dynamic interrelations between real and digital factory visible and tangible. We argue that our learning system does not work as a stand-alone solution, but should fit into existing academic and advanced training curricula.

A Study of the Relationship between Iranian EFL Learners' Level of Spatial Intelligence and Their Performance on Analytical and Perceptual Cloze Tests

ERIC Educational Resources Information Center

Ahmadian, Moussa; Jalilian, Vahid

2012-01-01

During the last two decades, Gardner's theory of multiple intelligences with its emphasis on learner variables has been appreciated in language learning. Spatial intelligence, as one domain of the multiple structures of intelligence, which is thought to play a great role in reading, writing, and literacy, particularly in L2 learning, has not…

Generalizing on Multiple Grounds: Performance Learning in Model-Based Troubleshooting

DTIC Science & Technology

1989-02-01

Aritificial Intelligence , 24, 1984. [Ble88] Guy E. Blelloch. Scan Primitives and Parallel Vector Models. PhD thesis, Artificial Intelligence Laboratory...Diagnostic reasoning based on strcture and behavior. Aritificial Intelligence , 24, 1984. [dK86] J. de Kleer. An assumption-based truth maintenance system...diagnosis. Aritificial Intelligence , 24. �. )3 94 BIBLIOGRAPHY [Ham87] Kristian J. Hammond. Learning to anticipate and avoid planning prob- lems

Development of cyberblog-based intelligent tutorial system to improve students learning ability algorithm

NASA Astrophysics Data System (ADS)

Wahyudin; Riza, L. S.; Putro, B. L.

2018-05-01

E-learning as a learning activity conducted online by the students with the usual tools is favoured by students. The use of computer media in learning provides benefits that are not owned by other learning media that is the ability of computers to interact individually with students. But the weakness of many learning media is to assume that all students have a uniform ability, when in reality this is not the case. The concept of Intelligent Tutorial System (ITS) combined with cyberblog application can overcome the weaknesses in neglecting diversity. An Intelligent Tutorial System-based Cyberblog application (ITS) is a web-based interactive application program that implements artificial intelligence which can be used as a learning and evaluation media in the learning process. The use of ITS-based Cyberblog in learning is one of the alternative learning media that is interesting and able to help students in measuring ability in understanding the material. This research will be associated with the improvement of logical thinking ability (logical thinking) of students, especially in algorithm subjects.

Selective Snapshot of State-of-the-Art Artificial Intelligence & Robotics with Reference to the Icarus Starship

NASA Astrophysics Data System (ADS)

Ellery, A.

Since the remarkable British Interplanetary Society starship study of the late 1970s - Daedalus - there have been significant developments in the areas of artificial intelligence and robotics. These will be critical technologies for any starship as indeed they are for the current generation of exploratory spacecraft and in-situ planetary robotic explorers. Although early visions of truly intelligent robots have yet to materialize (reasons for which will be outlined), there are nonetheless revolutionary developments which have attempted to address at least some of these earlier unperceived deficiencies. The current state of the art comprises a number of separate strands of research which provide components of robotic intelligence though no over- arching approach has been forthcoming. The first question to be considered is the level of intelligent functionality required to support a long-duration starship mission. This will, at a minimum, need to be extensive imposed by the requirement for complex reconfigurability and repair. The second question concerns the tools that we have at our disposal to implement the required intelligent functions of the starship. These are based on two very different approaches - good old-fashioned artificial intelligence (GOFAI) based on logical theorem-proving and knowledge-encoding recently augmented by modal, temporal, circumscriptive and fuzzy logics to address the well-known “frame problem”; and the more recent soft computing approaches based on artificial neural networks, evolutionary algorithms and immunity models and their variants to implement learning. The former has some flight heritage through the Remote Agent architecture whilst the latter has yet to be deployed on any space mission. However, the notion of reconfigurable hardware of recent interest in the space community warrants the use of evolutionary algorithms and neural networks implemented on field programmable gate array technology, blurring the distinction between hardware and software. The primary question in space engineering has traditionally been one of predictability and controllability which online learning compromises. A further factor to be accounted for is the notion that intelligence is derived primarily from robot-environment interaction which stresses the sensory and actuation capabilities (exemplified by the behavioural or situated robotics paradigm). One major concern is whether the major deficiency of current methods in terms of lack of scalability can be overcome using a highly distributed approach rather than the hierarchical approach suggested by the NASREM architecture. It is contended here that a mixed solution will be required where a priori programming is augmented by a posteriori learning resembling the biological distinction between fixed genetically inherited and learned neurally implemented behaviour in animals. In particular, a biomimetic approach is proferred which exploits the neural processes and architecture of the human brain through the use of forward models which attempts to marry the conflicting requirements of learning with predictability. Some small-scale efforts in this direction will be outlined.

Rule-based mechanisms of learning for intelligent adaptive flight control

NASA Technical Reports Server (NTRS)

Handelman, David A.; Stengel, Robert F.

1990-01-01

How certain aspects of human learning can be used to characterize learning in intelligent adaptive control systems is investigated. Reflexive and declarative memory and learning are described. It is shown that model-based systems-theoretic adaptive control methods exhibit attributes of reflexive learning, whereas the problem-solving capabilities of knowledge-based systems of artificial intelligence are naturally suited for implementing declarative learning. Issues related to learning in knowledge-based control systems are addressed, with particular attention given to rule-based systems. A mechanism for real-time rule-based knowledge acquisition is suggested, and utilization of this mechanism within the context of failure diagnosis for fault-tolerant flight control is demonstrated.

National Intelligence University’s Role in Interagency Research: Recommendations from the Intelligence Community

DTIC Science & Technology

2013-01-01

outreach, and (4) social science and historical research/lessons learned . In some instances, the research entity fit into more than one category. We...Bureau of Intelligence and Research (INR) and the Analytic Outreach Initiative (AOI) at ODNI. Social science and historical research/lessons learned ...its coordination efforts, CSIR was interested in learning more about potential interagency research partners and how collaboration could be improved

Research and Conceptualization of Ontologies in Intelligent Learning Systems

ERIC Educational Resources Information Center

Deliyska, Boryana; Manoilov, Peter

2010-01-01

The intelligent learning systems provide direct customized instruction to the learners without the intervention of human tutors on the basis of Semantic Web resources. Principal roles use ontologies as instruments for modeling learning processes, learners, learning disciplines and resources. This paper examines the variety, relationships, and…

Integrating Organizational Learning and Business Praxis: A Case for Intelligent Project Management.

ERIC Educational Resources Information Center

Cavaleri, Steven A.; Fearon, David S.

2000-01-01

Project management provides a natural home for organizational learning, freeing it from mechanical processes. Organizational learning plays a critical role in intelligent project management, which combines manageability, performance outcomes of knowledge management, and innovation. Learning should be integrated into an organization's core…

Fixed and Growth Mindset in Education and How Grit Helps Students Persist in the Face of Adversity

ERIC Educational Resources Information Center

Hochanadel, Aaron; Finamore, Dora

2015-01-01

Students face a wealth of challenges in college for example a lack of support, sometimes making it difficult to persevere. However, in an academic environment that teaches grit and fosters growth, students can learn to persist. Those who believe intelligence is fixed and cannot be changed exert less effort to succeed. Students who persevere when…

Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

PubMed

Oudeyer, Pierre-Yves

2017-01-01

Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.

Assessing Student Learning through Multiple Intelligences.

ERIC Educational Resources Information Center

McClaskey, Janet

1995-01-01

Gives practical examples of multiple intelligences in the English classroom. Discusses Howard Gardner's "radicalism,""teaching" intelligence, teaching literature and multiple intelligences, and how a student developed strength in his own intelligences through poetry. (RS)

Understanding the Impact of a Half Day Learning Intervention on Emotional Intelligence Competencies: An Exploratory Study

ERIC Educational Resources Information Center

Carrick, Laurie Ann

2010-01-01

Empirical evidence has identified emotional intelligence competencies as part of the transformational leadership style. The development of emotional intelligence competencies has been reviewed in the context of a leadership development learning intervention encompassing the model of assessment, challenge and support. The exploratory study…

Multiple Intelligences and Language Learning Strategies: Investigating Possible Relations

ERIC Educational Resources Information Center

Akbari, Ramin; Hosseini, Kobra

2008-01-01

The present study was conducted to investigate the existence of any possible relationship between the use of language learning strategies and multiple intelligences' scores of foreign language learners of English. Ninety subjects participated in the study. To measure the participants' multiple intelligence scores, MIDAS, a commercially designed…

The Personal Intelligences: Promoting Social and Emotional Learning.

ERIC Educational Resources Information Center

Ellison, Launa

This book blends two of the multiple intelligences (intrapersonal and interpersonal) with current research on the brain and learning to create a new foundation for K-8 classrooms. It shares a teacher's classroom practices linking brain functions with the development of interpersonal and intrapersonal intelligence. Nine chapters include (1)…

What have we learned about intelligent transportation systems? Chapter 2, What have we learned about freeway incident and emergency management and electronic toll collection?

DOT National Transportation Integrated Search

2000-12-01

The intelligent infrastructure is often the most visible manifestation of intelligent transportation systems (ITS) along with roads, freeways, and incident management is often among the first ITS elements implemented. They can significantly contribut...

Fluid Intelligence and Discriminative Operant Learning of Reinforcement Contingencies in a Fixed Ratio 3 Schedule

ERIC Educational Resources Information Center

Lozano, J. H.; Hernandez, J. M.; Rubio, V. J.; Santacreu, J.

2011-01-01

Although intelligence has traditionally been identified as "the ability to learn" (Peterson, 1925), this relationship has been questioned in simple operant learning tasks (Spielberger, 1962). Nevertheless, recent pieces of research have demonstrated a strong and significant correlation between associative learning measures and intelligence…

Effect of promoting self-esteem by participatory learning process on emotional intelligence among early adolescents.

PubMed

Munsawaengsub, Chokchai; Yimklib, Somkid; Nanthamongkolchai, Sutham; Apinanthavech, Suporn

2009-12-01

To study the effect of promoting self-esteem by participatory learning program on emotional intelligence among early adolescents. The quasi-experimental study was conducted in grade 9 students from two schools in Bangbuathong district, Nonthaburi province. Each experimental and comparative group consisted of 34 students with the lowest score of emotional intelligence. The instruments were questionnaires, Program to Develop Emotional Intelligence and Handbook of Emotional Intelligence Development. The experimental group attended 8 participatory learning activities in 4 weeks to Develop Emotional Intelligence while the comparative group received the handbook for self study. Assessment the effectiveness of program was done by pre-test and post-test immediately and 4 weeks apart concerning the emotional intelligence. Implementation and evaluation was done during May 24-August 12, 2005. Data were analyzed by frequency, percentage, mean, standard deviation, Chi-square, independent sample t-test and paired sample t-test. Before program implementation, both groups had no statistical difference in mean score of emotional intelligence. After intervention, the experimental group had higher mean score of emotional intelligence both immediately and 4 weeks later with statistical significant (p = 0.001 and < 0.001). At 4 weeks after experiment, the mean score in experimental group was higher than the mean score at immediate after experiment with statistical significance (p < 0.001). The program to promote self-esteem by participatory learning process could enhance the emotional intelligence in early-adolescent. This program could be modified and implemented for early adolescent in the community.

Iranian EFL Learners' Emotional Intelligence, Learning Styles, Strategy Use, and Their L2 Achievement

ERIC Educational Resources Information Center

Afshar, Hassan Soodmand; Tofighi, Somayyeh; Hamazavi, Raouf

2016-01-01

The idea that language learning is facilitated or inhibited by a multitude of factors has prompted scholars in the field to investigate variables considered to be crucial in the process of second or foreign language learning. This study investigated relationships between emotional intelligence, learning style, language learning strategy use, and…

An Intelligent Learning Diagnosis System for Web-Based Thematic Learning Platform

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Liu, Ming-Chou; Chu, San-Shine; Cheng, Chih-Lun

2007-01-01

This work proposes an intelligent learning diagnosis system that supports a Web-based thematic learning model, which aims to cultivate learners' ability of knowledge integration by giving the learners the opportunities to select the learning topics that they are interested, and gain knowledge on the specific topics by surfing on the Internet to…

Hypothesis: the hospital learning environment impedes students' acquisition of reflectivity and medical professionalism.

PubMed

Benbassat, Jochanan

2018-02-24

Undergraduate clinical education follows the "bedside" tradition that exposes students to inpatients. However, the hospital learning environment has two main limitations. First, most inpatients require acute care, and students may complete their training without seeing patients with frequent non-emergent and chronic diseases that are managed in outpatient settings. Second, students rarely cope with diagnostic problems, because most inpatients are diagnosed in the community or the emergency room. These limitations have led some medical schools to offer longitudinal integrated clerkships in community settings instead of hospital block clerkship rotations. In this paper, I propose the hypothesis that the hospital learning environment has a third limitation: it causes students' distress and delays their development of reflectivity and medical professionalism. This hypothesis is supported by evidence that (a) the clinical learning environment, rather than students' personality traits, is the major driver of students' distress, and (b) the development of attributes, such as moral reasoning, empathy, emotional intelligence and tolerance of uncertainty that are included in the definitions of both reflectivity and medical professionalism, is arrested during undergraduate medical training. Future research may test the proposed hypothesis by comparing students' development of these attributes during clerkships in hospital wards with that during longitudinal clerkships in community settings.

Learning classifier systems for single and multiple mobile robots in unstructured environments

NASA Astrophysics Data System (ADS)

Bay, John S.

1995-12-01

The learning classifier system (LCS) is a learning production system that generates behavioral rules via an underlying discovery mechanism. The LCS architecture operates similarly to a blackboard architecture; i.e., by posted-message communications. But in the LCS, the message board is wiped clean at every time interval, thereby requiring no persistent shared resource. In this paper, we adapt the LCS to the problem of mobile robot navigation in completely unstructured environments. We consider the model of the robot itself, including its sensor and actuator structures, to be part of this environment, in addition to the world-model that includes a goal and obstacles at unknown locations. This requires a robot to learn its own I/O characteristics in addition to solving its navigation problem, but results in a learning controller that is equally applicable, unaltered, in robots with a wide variety of kinematic structures and sensing capabilities. We show the effectiveness of this LCS-based controller through both simulation and experimental trials with a small robot. We then propose a new architecture, the Distributed Learning Classifier System (DLCS), which generalizes the message-passing behavior of the LCS from internal messages within a single agent to broadcast massages among multiple agents. This communications mode requires little bandwidth and is easily implemented with inexpensive, off-the-shelf hardware. The DLCS is shown to have potential application as a learning controller for multiple intelligent agents.

The application of multiple intelligence approach to the learning of human circulatory system

NASA Astrophysics Data System (ADS)

Kumalasari, Lita; Yusuf Hilmi, A.; Priyandoko, Didik

2017-11-01

The purpose of this study is to offer an alternative teaching approach or strategies which able to accommodate students’ different ability, intelligence and learning style. Also can gives a new idea for the teacher as a facilitator for exploring how to teach the student in creative ways and more student-center activities, for a lesson such as circulatory system. This study was carried out at one private school in Bandung involved eight students to see their responses toward the lesson that delivered by using Multiple Intelligence approach which is include Linguistic, Logical-Mathematical, Visual-Spatial, Musical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Naturalistic. Students were test by using MI test based on Howard Gardner’s MI model to see their dominant intelligence. The result showed the percentage of top three ranks of intelligence are Bodily-Kinesthetic (73%), Visual-Spatial (68%), and Logical-Mathematical (61%). The learning process is given by using some different multimedia and activities to engaged their learning style and intelligence such as mini experiment, short clip, and questions. Student response is given by using self-assessment and the result is all students said the lesson gives them a knowledge and skills that useful for their life, they are clear with the explanation given, they didn’t find difficulties to understand the lesson and can complete the assignment given. At the end of the study, it is reveal that the students who are learned by Multiple Intelligence instructional approach have more enhance to the lesson given. It’s also found out that the students participated in the learning process which Multiple Intelligence approach was applied enjoyed the activities and have great fun.

Intelligence: new findings and theoretical developments.

PubMed

Nisbett, Richard E; Aronson, Joshua; Blair, Clancy; Dickens, William; Flynn, James; Halpern, Diane F; Turkheimer, Eric

2012-01-01

We review new findings and new theoretical developments in the field of intelligence. New findings include the following: (a) Heritability of IQ varies significantly by social class. (b) Almost no genetic polymorphisms have been discovered that are consistently associated with variation in IQ in the normal range. (c) Much has been learned about the biological underpinnings of intelligence. (d) "Crystallized" and "fluid" IQ are quite different aspects of intelligence at both the behavioral and biological levels. (e) The importance of the environment for IQ is established by the 12-point to 18-point increase in IQ when children are adopted from working-class to middle-class homes. (f) Even when improvements in IQ produced by the most effective early childhood interventions fail to persist, there can be very marked effects on academic achievement and life outcomes. (g) In most developed countries studied, gains on IQ tests have continued, and they are beginning in the developing world. (h) Sex differences in aspects of intelligence are due partly to identifiable biological factors and partly to socialization factors. (i) The IQ gap between Blacks and Whites has been reduced by 0.33 SD in recent years. We report theorizing concerning (a) the relationship between working memory and intelligence, (b) the apparent contradiction between strong heritability effects on IQ and strong secular effects on IQ, (c) whether a general intelligence factor could arise from initially largely independent cognitive skills, (d) the relation between self-regulation and cognitive skills, and (e) the effects of stress on intelligence.

Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.

PubMed

Xu, Bin; Sun, Fuchun

2018-02-01

This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.

Learning Effects of Interactive Whiteboard Pedagogy for Students in Taiwan from the Perspective of Multiple Intelligences

ERIC Educational Resources Information Center

Chen, Hong-Ren; Chiang, Chih-Hao; Lin, Wen-Shan

2013-01-01

With the rapid progress in information technology, interactive whiteboards have become IT-integrated in teaching activities. The theory of multiple intelligences argues that every person possesses multiple intelligences, emphasizing learners' cognitive richness and the possible role of these differences in enhanced learning. This study is the…

The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

ERIC Educational Resources Information Center

Hali, Nur Ihsan

2017-01-01

This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…

Prerequisites for Emotional Intelligence Formation in Second Language Learning and Career Choice

ERIC Educational Resources Information Center

Baklashova, Tatiana A.; Galishnikova, Elena M.; Khafizova, Liliya A.

2016-01-01

The relevance of the topic is due to the enhancing role of emotional intelligence in second language learning. The article aims to substantiate that emotional intelligence (EI) strengthens training quality of future professionals, gives it an emotional color, and thereby increases a variety of intellectual skills. The leading methodical approaches…

Validating the Learning Disability Screening Questionnaire against the Weschler Adult Intelligence Scale, Fourth Edition

ERIC Educational Resources Information Center

McKenzie, Karen; Sharples, Phil; Murray, Aja L.

2015-01-01

The Learning Disability Screening Questionnaire (LDSQ), a brief screening tool for intellectual disability, was originally validated against the Weschler Adult Intelligence Scale, Third Edition (WAIS-III), which was superseded by the Weschler Adult Intelligence Scale, Fourth Edition (WAIS-IV) in the United Kingdom in 2010. This study examines the…

Generalizing Automated Detection of the Robustness of Student Learning in an Intelligent Tutor for Genetics

ERIC Educational Resources Information Center

Baker, Ryan S. J. d.; Corbett, Albert T.; Gowda, Sujith M.

2013-01-01

Recently, there has been growing emphasis on supporting robust learning within intelligent tutoring systems, assessed by measures such as transfer to related skills, preparation for future learning, and longer term retention. It has been shown that different pedagogical strategies promote robust learning to different degrees. However, the student…

Training Strategies for the Twenty-First Century: Using Recent Research on Learning To Enhance Training.

ERIC Educational Resources Information Center

Dwyer, Brian M.

2002-01-01

Discusses a new training model that takes into account the diversity of learners and the emotional, physical and social environmental conditions essential for lifelong learning. Considers how the brain learns and functions, brain-based learning, multiple intelligence, and emotional intelligence as well as personal reflection. (LRW)

An Intelligent Computer Assisted Language Learning System for Arabic Learners

ERIC Educational Resources Information Center

Shaalan, Khaled F.

2005-01-01

This paper describes the development of an intelligent computer-assisted language learning (ICALL) system for learning Arabic. This system could be used for learning Arabic by students at primary schools or by learners of Arabic as a second or foreign language. It explores the use of Natural Language Processing (NLP) techniques for learning…

Think Pair Share Using Realistic Mathematics Education Approach in Geometry Learning

NASA Astrophysics Data System (ADS)

Afthina, H.; Mardiyana; Pramudya, I.

2017-09-01

This research aims to determine the impact of mathematics learning applying Think Pair Share (TPS) using Realistic Mathematics Education (RME) viewed from mathematical-logical intelligence in geometry learning. Method that used in this research is quasi experimental research The result of this research shows that (1) mathematics achievement applying TPS using RME approach gives a better result than those applying direct learning model; (2) students with high mathematical-logical intelligence can reach a better mathematics achievement than those with average and low one, whereas students with average mathematical-logical intelligence can reach a better achievement than those with low one; (3) there is no interaction between learning model and the level of students’ mathematical-logical intelligence in giving a mathematics achievement. The impact of this research is that TPS model using RME approach can be applied in mathematics learning so that students can learn more actively and understand the material more, and mathematics learning become more meaningful. On the other hand, internal factors of students must become a consideration toward the success of students’ mathematical achievement particularly in geometry material.

Prior exposure to a reverberant listening environment improves speech intelligibility in adult cochlear implant listeners.

PubMed

Srinivasan, Nirmal Kumar; Tobey, Emily A; Loizou, Philipos C

2016-01-01

The goal of this study is to investigate whether prior exposure to reverberant listening environment improves speech intelligibility of adult cochlear implant (CI) users. Six adult CI users participated in this study. Speech intelligibility was measured in five different simulated reverberant listening environments with two different speech corpuses. Within each listening environment, prior exposure was varied by either having the same environment across all trials (blocked presentation) or having different environment from trial to trial (unblocked). Speech intelligibility decreased as reverberation time increased. Although substantial individual variability was observed, all CI listeners showed an increase in the blocked presentation condition as compared to the unblocked presentation condition for both speech corpuses. Prior listening exposure to a reverberant listening environment improves speech intelligibility in adult CI listeners. Further research is required to understand the underlying mechanism of adaptation to listening environment.

Hospital-based nurses' perceptions of the adoption of Web 2.0 tools for knowledge sharing, learning, social interaction and the production of collective intelligence.

PubMed

Lau, Adela S M

2011-11-11

Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson's correlation analysis and t tests were used for data analysis. Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P < .05). Behavioral intention was positively correlated with attitude (r = .72, P < .05), perceived behavioral control (r = .58, P < .05), and subjective norm (r = .45, P < .05). In their decomposed constructs, perceived usefulness (r = .7, P < .05), relative advantage (r = .64, P < .05), and compatibility (r = .60,P < .05) were positively correlated with attitude, but perceived ease of use was not significantly correlated (r = .004, P < .05) with it. Peer (r = .47, P < .05), senior management (r = .24,P < .05), and hospital (r = .45, P < .05) influences had positive correlations with subjective norm. Resource (r = .41,P < .05) and technological (r = .69,P < .05) conditions were positively correlated with perceived behavioral control. The identified behavioral perceptions may further health policy makers' understanding of nurses' concerns regarding and barriers to the adoption of Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence.

Hospital-Based Nurses’ Perceptions of the Adoption of Web 2.0 Tools for Knowledge Sharing, Learning, Social Interaction and the Production of Collective Intelligence

PubMed Central

2011-01-01

Background Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. Objectives The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. Methods The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson’s correlation analysis and t tests were used for data analysis. Results Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P < .05). Behavioral intention was positively correlated with attitude (r = .72, P < .05), perceived behavioral control (r = .58, P < .05), and subjective norm (r = .45, P < .05). In their decomposed constructs, perceived usefulness (r = .7, P < .05), relative advantage (r = .64, P < .05), and compatibility (r = .60, P < .05) were positively correlated with attitude, but perceived ease of use was not significantly correlated (r = .004, P < .05) with it. Peer (r = .47, P < .05), senior management (r = .24, P < .05), and hospital (r = .45, P < .05) influences had positive correlations with subjective norm. Resource (r = .41, P < .05) and technological (r = .69, P < .05) conditions were positively correlated with perceived behavioral control. Conclusions The identified behavioral perceptions may further health policy makers’ understanding of nurses’ concerns regarding and barriers to the adoption of Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence. PMID:22079851

Foreign language learning in immersive virtual environments

NASA Astrophysics Data System (ADS)

Chang, Benjamin; Sheldon, Lee; Si, Mei; Hand, Anton

2012-03-01

Virtual reality has long been used for training simulations in fields from medicine to welding to vehicular operation, but simulations involving more complex cognitive skills present new design challenges. Foreign language learning, for example, is increasingly vital in the global economy, but computer-assisted education is still in its early stages. Immersive virtual reality is a promising avenue for language learning as a way of dynamically creating believable scenes for conversational training and role-play simulation. Visual immersion alone, however, only provides a starting point. We suggest that the addition of social interactions and motivated engagement through narrative gameplay can lead to truly effective language learning in virtual environments. In this paper, we describe the development of a novel application for teaching Mandarin using CAVE-like VR, physical props, human actors and intelligent virtual agents, all within a semester-long multiplayer mystery game. Students travel (virtually) to China on a class field trip, which soon becomes complicated with intrigue and mystery surrounding the lost manuscript of an early Chinese literary classic. Virtual reality environments such as the Forbidden City and a Beijing teahouse provide the setting for learning language, cultural traditions, and social customs, as well as the discovery of clues through conversation in Mandarin with characters in the game.

Emotionally Evocative Environments for Training

DTIC Science & Technology

2002-01-01

Sense of Our Senses,” Howard Hughes Medical Institute Report, pp. 48-55, 1995. Ulate, S. O., “ The Impact of Emotional Arousal on Learning in Virtual...paper describes a project currently in progress at the University of Southern California’s Institute for Creative Technologies (ICT). Much of the ...research at ICT involves developing better graphics, sound and artificial intelligence to be used in creating the next generation of training tools for

Intelligent Tutoring Methods for Optimizing Learning Outcomes with Embedded Training

DTIC Science & Technology

2009-10-01

after action review. Particularly with free - play virtual environments, it is important to constrain the development task for constructing an...evaluation approach. Attempts to model all possible variations of correct performance can be prohibitive in free - play scenarios, and so for such conditions...member R for proper execution during free - play execution. In the first tier, the evaluation must know when it applies, or more specifically, when

Artificial Intelligence in Cardiology.

PubMed

Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T

2018-06-12

Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Mathematical intelligence developed in math learning with classical backsound music of the classical era

NASA Astrophysics Data System (ADS)

Karlimah

2018-05-01

This study examines the application of classical music backsound in mathematics learning. The method used is quasi experimental design nonequivalent pretest-posttest control group in elementary school students in Tasikmalaya city, Indonesia. The results showed that classical music contributed significantly to the mathematical intelligence of elementary school students. The mathematical intelligence shown is in the cognitive ability ranging from the level of knowledge to evaluation. High level mathematical intelligence is shown by students in reading and writing integers with words and numbers. The low level of mathematical intelligence exists in projecting the story into a mathematical problem. The implication of this research is the use of classical music backsound on learning mathematics should pay attention to the level of difficulty of mathematics material being studied.

Teaching for Multiple Intelligences in Undergraduate Education

NASA Astrophysics Data System (ADS)

Denny, Margaret

Multiple intelligences theory has only recently entered the teaching and learning dialogue in education and research. It is argued that despite the rhetoric of a student centred approach, nurse education remains wedded to conventional teaching approaches, which fail to engage with the individual and unwittingly silence the student's voice. This study examines the concept of Multiple Intelligences (MI) and outlines Gardner's contention that the brain functions using eight intelligences, which can be employed to improve learning at an individual level.

Learning Negotiation Policies Using IB3 and Bayesian Networks

NASA Astrophysics Data System (ADS)

Nalepa, Gislaine M.; Ávila, Bráulio C.; Enembreck, Fabrício; Scalabrin, Edson E.

This paper presents an intelligent offer policy in a negotiation environment, in which each agent involved learns the preferences of its opponent in order to improve its own performance. Each agent must also be able to detect drifts in the opponent's preferences so as to quickly adjust itself to their new offer policy. For this purpose, two simple learning techniques were first evaluated: (i) based on instances (IB3) and (ii) based on Bayesian Networks. Additionally, as its known that in theory group learning produces better results than individual/single learning, the efficiency of IB3 and Bayesian classifier groups were also analyzed. Finally, each decision model was evaluated in moments of concept drift, being the drift gradual, moderate or abrupt. Results showed that both groups of classifiers were able to effectively detect drifts in the opponent's preferences.

Supporting tactical intelligence using collaborative environments and social networking

NASA Astrophysics Data System (ADS)

Wollocko, Arthur B.; Farry, Michael P.; Stark, Robert F.

2013-05-01

Modern military environments place an increased emphasis on the collection and analysis of intelligence at the tactical level. The deployment of analytical tools at the tactical level helps support the Warfighter's need for rapid collection, analysis, and dissemination of intelligence. However, given the lack of experience and staffing at the tactical level, most of the available intelligence is not exploited. Tactical environments are staffed by a new generation of intelligence analysts who are well-versed in modern collaboration environments and social networking. An opportunity exists to enhance tactical intelligence analysis by exploiting these personnel strengths, but is dependent on appropriately designed information sharing technologies. Existing social information sharing technologies enable users to publish information quickly, but do not unite or organize information in a manner that effectively supports intelligence analysis. In this paper, we present an alternative approach to structuring and supporting tactical intelligence analysis that combines the benefits of existing concepts, and provide detail on a prototype system embodying that approach. Since this approach employs familiar collaboration support concepts from social media, it enables new-generation analysts to identify the decision-relevant data scattered among databases and the mental models of other personnel, increasing the timeliness of collaborative analysis. Also, the approach enables analysts to collaborate visually to associate heterogeneous and uncertain data within the intelligence analysis process, increasing the robustness of collaborative analyses. Utilizing this familiar dynamic collaboration environment, we hope to achieve a significant reduction of time and skill required to glean actionable intelligence in these challenging operational environments.

An Examination of Multiple Intelligence Domains and Learning Styles of Pre-Service Mathematics Teachers: Their Reflections on Mathematics Education

ERIC Educational Resources Information Center

Ozgen, Kemal; Tataroglu, Berna; Alkan, Huseyin

2011-01-01

The present study aims to identify pre-service mathematics teachers' multiple intelligence domains and learning style profiles, and to establish relationships between them. Employing the survey model, the study was conducted with the participation of 243 pre-service mathematics teachers. The study used the "multiple intelligence domains…

Relationships between a Social-Emotional Learning Program and Emotional Intelligence in Middle School Students

ERIC Educational Resources Information Center

Brown, Katherine Marie

2013-01-01

This study examined the relationships between a social-emotional learning program and the 5 dimensions of emotional intelligence and whether the relationships were moderated by gender. The problem addressed in the study was the lack of research focused on the development of emotional intelligence at the middle school level. The participants…

Multi-Domain, Multi-Method Measures of Metacognitive Activity: What Is All the Fuss about Metacognition ... Indeed?

ERIC Educational Resources Information Center

Meijer, Joost; Veenman, Marcel V. J.; van Hout-Wolters, Bernadette

2012-01-01

Studies about metacognition, intelligence and learning have rendered equivocal results. The mixed model assumes joint as well as independent influences of intelligence and metacognition on learning results. In this study, intelligence was measured by standard tests for reasoning, spatial ability and memory. Participants were 13-year-old school…

The Relationship between Principal Emotional Intelligence and the School as a Learning Organization

ERIC Educational Resources Information Center

DeRoberto, Thomas

2011-01-01

The purpose of this study was to determine the nature of the relationship between the emotional intelligence of the school principal and the school as a learning organization. These constructs originated in the business world and have recently been examined within the context of education. Studies on principal emotional intelligence have shown the…

An Empirical Examination of the Association between Multiple Intelligences and Language Learning Self-Efficacy among TEFL University Students

ERIC Educational Resources Information Center

Moafian, Fatemeh; Ebrahimi, Mohammad Reza

2015-01-01

The current study investigated the association between multiple intelligences and language learning efficacy expectations among TEFL (Teaching English as a Foreign Language) university students. To fulfill the aim of the study, 108 junior and senior TEFL students were asked to complete the "Multiple Intelligence Developmental Assessment…

Development and Evaluation of Intelligent Agent-Based Teaching Assistant in e-Learning Portals

ERIC Educational Resources Information Center

Rouhani, Saeed; Mirhosseini, Seyed Vahid

2015-01-01

Today, several educational portals established by organizations to enhance web E-learning. Intelligence agent's usage is necessary to improve the system's quality and cover limitations such as face-to-face relation. In this research, after finding two main approaches in this field that are fundamental use of intelligent agents in systems design…

Case-Based Planning: An Integrated Theory of Planning, Learning and Memory

DTIC Science & Technology

1986-10-01

rtvoeoo oldo II nocomtmry and Idonltly by block numbor) planning Case-based reasoning learning Artificial Intelligence 20. ABSTRACT (Conllnum...Computational Model of Analogical Prob- lem Solving, Proceedings of the Seventh International Joint Conference on Artificial Intelligence ...Understanding and Generalizing Plans., Proceedings of the Eight Interna- tional Joint Conference on Artificial Intelligence , IJCAI, Karlsrhue, Germany

Implications for Intelligent Tutoring Systems for Research and Practice in Foreign Language Learning, NFLC Occasional Papers.

ERIC Educational Resources Information Center

Ginsberg, Ralph B.

Most of the now commonplace computer-assisted instruction (CAI) uses computers to increase the capacity to perform logical, numerical, and symbolic computations. However, computers are an interactive and potentially intelligent medium. The implications of artificial intelligence (AI) for learning are more radical than those for traditional CAI. AI…

Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

ERIC Educational Resources Information Center

Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

2010-01-01

Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

Developing an Intelligent Diagnosis and Assessment E-Learning Tool for Introductory Programming

ERIC Educational Resources Information Center

Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta

2008-01-01

Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…

On Using Intelligent Computer-Assisted Language Learning in Real-Life Foreign Language Teaching and Learning

ERIC Educational Resources Information Center

Amaral, Luiz A.; Meurers, Detmar

2011-01-01

This paper explores the motivation and prerequisites for successful integration of Intelligent Computer-Assisted Language Learning (ICALL) tools into current foreign language teaching and learning (FLTL) practice. We focus on two aspects, which we argue to be important for effective ICALL system development and use: (i) the relationship between…

Your Verbal Zone: An Intelligent Computer-Assisted Language Learning Program in Support of Turkish Learners' Vocabulary Learning

ERIC Educational Resources Information Center

Esit, Omer

2011-01-01

This study investigated the effectiveness of an intelligent computer-assisted language learning (ICALL) program on Turkish learners' vocabulary learning. Within the scope of this research, an ICALL application with a morphological analyser (Your Verbal Zone, YVZ) was developed and used in an English language preparatory class to measure its…

Mindset about Intelligence and Meaningful and Mindful Effort: It's Not My Hardest Class Any More!

ERIC Educational Resources Information Center

Wiersema, Janice A.; Licklider, Barbara; Thompson, Janette R.; Hendrich, Suzanne; Haynes, Cynthia; Thompson, Katherine

2015-01-01

College students' implicit theories (or mindsets) about intelligence can affect not only their motivations toward learning, but also their cognitive habits and behaviors while learning thus impacting academic achievement. In this paper we describe learning experiences we used with our learning community to 1) introduce students to the concept of…

Interindividual Differences in Learning Performance: The Effects of Age, Intelligence, and Strategic Task Approach

ERIC Educational Resources Information Center

Kliegel, Matthias; Altgassen, Mareike

2006-01-01

The present study investigated fluid and crystallized intelligence as well as strategic task approaches as potential sources of age-related differences in adult learning performance. Therefore, 45 young and 45 old adults were asked to learn pictured objects. Overall, young participants outperformed old participants in this learning test. However,…

Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

NASA Astrophysics Data System (ADS)

Vaccaro, James M.; Yaworsky, Paul S.

1999-06-01

Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

Model learning for robot control: a survey.

PubMed

Nguyen-Tuong, Duy; Peters, Jan

2011-11-01

Models are among the most essential tools in robotics, such as kinematics and dynamics models of the robot's own body and controllable external objects. It is widely believed that intelligent mammals also rely on internal models in order to generate their actions. However, while classical robotics relies on manually generated models that are based on human insights into physics, future autonomous, cognitive robots need to be able to automatically generate models that are based on information which is extracted from the data streams accessible to the robot. In this paper, we survey the progress in model learning with a strong focus on robot control on a kinematic as well as dynamical level. Here, a model describes essential information about the behavior of the environment and the influence of an agent on this environment. In the context of model-based learning control, we view the model from three different perspectives. First, we need to study the different possible model learning architectures for robotics. Second, we discuss what kind of problems these architecture and the domain of robotics imply for the applicable learning methods. From this discussion, we deduce future directions of real-time learning algorithms. Third, we show where these scenarios have been used successfully in several case studies.

What Can Reinforcement Learning Teach Us About Non-Equilibrium Quantum Dynamics

NASA Astrophysics Data System (ADS)

Bukov, Marin; Day, Alexandre; Sels, Dries; Weinberg, Phillip; Polkovnikov, Anatoli; Mehta, Pankaj

Equilibrium thermodynamics and statistical physics are the building blocks of modern science and technology. Yet, our understanding of thermodynamic processes away from equilibrium is largely missing. In this talk, I will reveal the potential of what artificial intelligence can teach us about the complex behaviour of non-equilibrium systems. Specifically, I will discuss the problem of finding optimal drive protocols to prepare a desired target state in quantum mechanical systems by applying ideas from Reinforcement Learning [one can think of Reinforcement Learning as the study of how an agent (e.g. a robot) can learn and perfect a given policy through interactions with an environment.]. The driving protocols learnt by our agent suggest that the non-equilibrium world features possibilities easily defying intuition based on equilibrium physics.

Research on knowledge representation, machine learning, and knowledge acquisition

NASA Technical Reports Server (NTRS)

Buchanan, Bruce G.

1987-01-01

Research in knowledge representation, machine learning, and knowledge acquisition performed at Knowledge Systems Lab. is summarized. The major goal of the research was to develop flexible, effective methods for representing the qualitative knowledge necessary for solving large problems that require symbolic reasoning as well as numerical computation. The research focused on integrating different representation methods to describe different kinds of knowledge more effectively than any one method can alone. In particular, emphasis was placed on representing and using spatial information about three dimensional objects and constraints on the arrangement of these objects in space. Another major theme is the development of robust machine learning programs that can be integrated with a variety of intelligent systems. To achieve this goal, learning methods were designed, implemented and experimented within several different problem solving environments.

Artificial intelligence framework for simulating clinical decision-making: a Markov decision process approach.

PubMed

Bennett, Casey C; Hauser, Kris

2013-01-01

In the modern healthcare system, rapidly expanding costs/complexity, the growing myriad of treatment options, and exploding information streams that often do not effectively reach the front lines hinder the ability to choose optimal treatment decisions over time. The goal in this paper is to develop a general purpose (non-disease-specific) computational/artificial intelligence (AI) framework to address these challenges. This framework serves two potential functions: (1) a simulation environment for exploring various healthcare policies, payment methodologies, etc., and (2) the basis for clinical artificial intelligence - an AI that can "think like a doctor". This approach combines Markov decision processes and dynamic decision networks to learn from clinical data and develop complex plans via simulation of alternative sequential decision paths while capturing the sometimes conflicting, sometimes synergistic interactions of various components in the healthcare system. It can operate in partially observable environments (in the case of missing observations or data) by maintaining belief states about patient health status and functions as an online agent that plans and re-plans as actions are performed and new observations are obtained. This framework was evaluated using real patient data from an electronic health record. The results demonstrate the feasibility of this approach; such an AI framework easily outperforms the current treatment-as-usual (TAU) case-rate/fee-for-service models of healthcare. The cost per unit of outcome change (CPUC) was $189 vs. $497 for AI vs. TAU (where lower is considered optimal) - while at the same time the AI approach could obtain a 30-35% increase in patient outcomes. Tweaking certain AI model parameters could further enhance this advantage, obtaining approximately 50% more improvement (outcome change) for roughly half the costs. Given careful design and problem formulation, an AI simulation framework can approximate optimal decisions even in complex and uncertain environments. Future work is described that outlines potential lines of research and integration of machine learning algorithms for personalized medicine. Copyright © 2012 Elsevier B.V. All rights reserved.

Academic Achievement from Using the Learning Medium Via a Tablet Device Based on Multiple Intelligences in Grade 1 Elementary Student.

PubMed

Nuallaong, Winitra; Nuallaong, Thanya; Preechadirek, Nongluck

2015-04-01

To measure academic achievement of the multiple intelligence-based learning medium via a tablet device. This is a quasi-experimental research study (non-randomized control group pretest-posttest design) in 62 grade 1 elementary students (33 males and 29 females). Thirty-one students were included in an experimental group using purposive sampling by choosing a student who had highest multiple intelligence test scores in logical-mathematic. Then, this group learned by the new learning medium via a tablet which the application matched to logical-mathematic multiple intelligence. Another 31 students were included in a control group using simple random sampling and then learning by recitation. Both groups did pre-test and post-test vocabulary. Thirty students in the experimental group and 24 students in the control group increased post-test scores (odds ratio = 8.75). Both groups made significant increasing in post-test scores. The experimental group increased 9.07 marks (95% CI 8.20-9.93) significantly higher than the control group which increased 4.39 marks (95% CI 3.06-5.72) (t = -6.032, df = 51.481, p < 0.001). Although learning from either multiple intelligence-based learning medium via a tablet or recitation can contribute academic achievement, learningfrom the new medium contributed more achievement than recitation. The new learning medium group had higher post-test scores 8.75 times than the recitation group. Therefore, the new learning medium is more effective than the traditional recitation in terms of academic achievement. This study has limitations because samples came from the same school. However, the previous study in Thailand did notfind a logical-mathematical multiple intelligence difference among schools. In the future, long-term research to find how the new learning medium affects knowledge retention will support the advantage for life-long learning.

Multi-agent Reinforcement Learning Model for Effective Action Selection

NASA Astrophysics Data System (ADS)

Youk, Sang Jo; Lee, Bong Keun

Reinforcement learning is a sub area of machine learning concerned with how an agent ought to take actions in an environment so as to maximize some notion of long-term reward. In the case of multi-agent, especially, which state space and action space gets very enormous in compared to single agent, so it needs to take most effective measure available select the action strategy for effective reinforcement learning. This paper proposes a multi-agent reinforcement learning model based on fuzzy inference system in order to improve learning collect speed and select an effective action in multi-agent. This paper verifies an effective action select strategy through evaluation tests based on Robocop Keep away which is one of useful test-beds for multi-agent. Our proposed model can apply to evaluate efficiency of the various intelligent multi-agents and also can apply to strategy and tactics of robot soccer system.

The Mediating Role of Organizational Learning in the Relationship of Organizational Intelligence and Organizational Agility.

PubMed

Bahrami, Mohammad Amin; Kiani, Mohammad Mehdi; Montazeralfaraj, Raziye; Zadeh, Hossein Fallah; Zadeh, Morteza Mohammad

2016-06-01

Organizational learning is defined as creating, absorbing, retaining, transferring, and application of knowledge within an organization. This article aims to examine the mediating role of organizational learning in the relationship of organizational intelligence and organizational agility. This analytical and cross-sectional study was conducted in 2015 at four teaching hospitals of Yazd city, Iran. A total of 370 administrative and medical staff contributed to the study. We used stratified-random method for sampling. Required data were gathered using three valid questionnaires including Alberkht (2003) organizational intelligence, Neefe (2001) organizational learning, and Sharifi and Zhang (1999) organizational agility questionnaires. Data analysis was done through R and SPSS 18 statistical software. The results showed that organizational learning acts as a mediator in the relationship of organizational intelligence and organizational agility (path coefficient = 0.943). Also, organizational learning has a statistical relationship with organizational agility (path coefficient = 0.382). Our findings suggest that the improvement of organizational learning abilities can affect an organization's agility which is crucial for its survival.

Adaptive quantum computation in changing environments using projective simulation

NASA Astrophysics Data System (ADS)

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-08-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks.

Adaptive quantum computation in changing environments using projective simulation

PubMed Central

Tiersch, M.; Ganahl, E. J.; Briegel, H. J.

2015-01-01

Quantum information processing devices need to be robust and stable against external noise and internal imperfections to ensure correct operation. In a setting of measurement-based quantum computation, we explore how an intelligent agent endowed with a projective simulator can act as controller to adapt measurement directions to an external stray field of unknown magnitude in a fixed direction. We assess the agent’s learning behavior in static and time-varying fields and explore composition strategies in the projective simulator to improve the agent’s performance. We demonstrate the applicability by correcting for stray fields in a measurement-based algorithm for Grover’s search. Thereby, we lay out a path for adaptive controllers based on intelligent agents for quantum information tasks. PMID:26260263

A Petri-net coordination model for an intelligent mobile robot

NASA Technical Reports Server (NTRS)

Wang, F.-Y.; Kyriakopoulos, K. J.; Tsolkas, A.; Saridis, G. N.

1990-01-01

The authors present a Petri net model of the coordination level of an intelligent mobile robot system (IMRS). The purpose of this model is to specify the integration of the individual efforts on path planning, supervisory motion control, and vision systems that are necessary for the autonomous operation of the mobile robot in a structured dynamic environment. This is achieved by analytically modeling the various units of the system as Petri net transducers and explicitly representing the task precedence and information dependence among them. The model can also be used to simulate the task processing and to evaluate the efficiency of operations and the responsibility of decisions in the coordination level of the IMRS. Some simulation results on the task processing and learning are presented.

Emotional Intelligence Instruction in a Pharmacy Communications Course

PubMed Central

Lust, Elaine; Moore, Frances C.

2006-01-01

Objectives To determine the benefits of incorporating emotional intelligence instruction into a required pharmacy communications course. Design Specific learning objectives were developed based upon the emotional intelligence framework and how it can be applied to pharmacy practice. Qualitative data on student perceptions were collected and analyzed using theme analysis. Assessment Students found instruction on emotional intelligence to be a positive experience. Students reported learning the taxonomy of emotional intelligence – a concept that previously was difficult for them to articulate or describe, and could use this knowledge in future pharmacy management situations. Students also recognized that their new knowledge of emotional intelligence would lead to better patient outcomes. Conclusion Students had positive perceptions of the importance of emotional intelligence. They valued its inclusion in the pharmacy curriculum and saw practical applications of emotional intelligence to the practice of pharmacy. PMID:17136149

Apparatus for multiprocessor-based control of a multiagent robot

NASA Technical Reports Server (NTRS)

Peters, II, Richard Alan (Inventor)

2009-01-01

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Digital Environment for Movement Control in Surgical Skill Training.

PubMed

Juanes, Juan A; Gómez, Juan J; Peguero, Pedro D; Ruisoto, Pablo

2016-06-01

Intelligent environments are increasingly becoming useful scenarios for handling computers. Technological devices are practical tools for learning and acquiring clinical skills as part of the medical training process. Within the framework of the advanced user interface, we present a technological application using Leap Motion, to enhance interaction with the user in the process of a laparoscopic surgical intervention and integrate the navigation through augmented reality images using manual gestures. Thus, we intend to achieve a more natural interaction with the objects that participate in a surgical intervention, which are augmented and related to the user's hand movements.

Septo-Optic Dysplasia

MedlinePlus

... children with SOD have normal intelligence, others have learning disabilities. Most, however, are developmentally delayed due to vision ... children with SOD have normal intelligence, others have learning disabilities. Most, however, are developmentally delayed due to vision ...

[Advances in the research of application of artificial intelligence in burn field].

PubMed

Li, H H; Bao, Z X; Liu, X B; Zhu, S H

2018-04-20

Artificial intelligence has been able to automatically learn and judge large-scale data to some extent. Based on database of a large amount of burn data and in-depth learning, artificial intelligence can assist burn surgeons to evaluate burn surface, diagnose burn depth, guide fluid supply during shock stage, and predict prognosis, with high accuracy. With the development of technology, artificial intelligence can provide more accurate information for burn surgeons to make clinical diagnosis and treatment strategies.

Data mining and education.

PubMed

Koedinger, Kenneth R; D'Mello, Sidney; McLaughlin, Elizabeth A; Pardos, Zachary A; Rosé, Carolyn P

2015-01-01

An emerging field of educational data mining (EDM) is building on and contributing to a wide variety of disciplines through analysis of data coming from various educational technologies. EDM researchers are addressing questions of cognition, metacognition, motivation, affect, language, social discourse, etc. using data from intelligent tutoring systems, massive open online courses, educational games and simulations, and discussion forums. The data include detailed action and timing logs of student interactions in user interfaces such as graded responses to questions or essays, steps in rich problem solving environments, games or simulations, discussion forum posts, or chat dialogs. They might also include external sensors such as eye tracking, facial expression, body movement, etc. We review how EDM has addressed the research questions that surround the psychology of learning with an emphasis on assessment, transfer of learning and model discovery, the role of affect, motivation and metacognition on learning, and analysis of language data and collaborative learning. For example, we discuss (1) how different statistical assessment methods were used in a data mining competition to improve prediction of student responses to intelligent tutor tasks, (2) how better cognitive models can be discovered from data and used to improve instruction, (3) how data-driven models of student affect can be used to focus discussion in a dialog-based tutoring system, and (4) how machine learning techniques applied to discussion data can be used to produce automated agents that support student learning as they collaborate in a chat room or a discussion board. © 2015 John Wiley & Sons, Ltd.

Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective

ERIC Educational Resources Information Center

Lytras, Miltiadis, Ed.; Naeve, Ambjorn, Ed.

2005-01-01

In the context of Knowledge Society, the convergence of knowledge and learning management is a critical milestone. "Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective" provides state-of-the art knowledge through a balanced theoretical and technological discussion. The semantic web perspective…

Developing Self-Regulated Learners through an Intelligent Tutoring System

ERIC Educational Resources Information Center

Kelly, Kim; Heffernan, Neil

2015-01-01

Intelligent tutoring systems have been developed to help students learn independently. However, students who are poor self-regulated learners often struggle to use these systems because they lack the skills necessary to learn independently. The field of psychology has extensively studied self-regulated learning and can provide strategies to…

Automatic Presentation of Sense-Specific Lexical Information in an Intelligent Learning System

ERIC Educational Resources Information Center

Eom, Soojeong

2012-01-01

Learning vocabulary and understanding texts present difficulty for language learners due to, among other things, the high degree of lexical ambiguity. By developing an intelligent tutoring system, this dissertation examines whether automatically providing enriched sense-specific information is effective for vocabulary learning and reading…

Adaptive Educational Software by Applying Reinforcement Learning

ERIC Educational Resources Information Center

Bennane, Abdellah

2013-01-01

The introduction of the intelligence in teaching software is the object of this paper. In software elaboration process, one uses some learning techniques in order to adapt the teaching software to characteristics of student. Generally, one uses the artificial intelligence techniques like reinforcement learning, Bayesian network in order to adapt…

Clinical teaching with emotional intelligence: A teaching toolbox

PubMed Central

Omid, Athar; Haghani, Fariba; Adibi, Peyman

2016-01-01

Background: Emotional intelligence (EI) helps humans to perceive their own and others’ emotions. It helps to make better interpersonal communication that consequently leads to an increase in everyday performance and professional career. Teaching, particularly teaching in the clinical environment, is among the professions that need a high level of EI due to its relevance to human interactions. Materials and Methods: We adopted EI competencies with characteristics of a good clinical teacher. As a result, we extracted 12 strategies and then reviewed the literatures relevant to these strategies. Results: In the present article, 12 strategies that a clinical teacher should follow to use EI in her/his teaching were described. Conclusion: To apply EI in clinical settings, a teacher should consider all the factors that can bring about a more positive emotional environment and social interactions. These factors will increase students’ learning, improve patients’ care, and maintain her/his well-being. In addition, he/she will be able to evaluate her/his teaching to improve its effectiveness. PMID:27904573

Rhythm Perception and Its Role in Perception and Learning of Dysrhythmic Speech.

PubMed

Borrie, Stephanie A; Lansford, Kaitlin L; Barrett, Tyson S

2017-03-01

The perception of rhythm cues plays an important role in recognizing spoken language, especially in adverse listening conditions. Indeed, this has been shown to hold true even when the rhythm cues themselves are dysrhythmic. This study investigates whether expertise in rhythm perception provides a processing advantage for perception (initial intelligibility) and learning (intelligibility improvement) of naturally dysrhythmic speech, dysarthria. Fifty young adults with typical hearing participated in 3 key tests, including a rhythm perception test, a receptive vocabulary test, and a speech perception and learning test, with standard pretest, familiarization, and posttest phases. Initial intelligibility scores were calculated as the proportion of correct pretest words, while intelligibility improvement scores were calculated by subtracting this proportion from the proportion of correct posttest words. Rhythm perception scores predicted intelligibility improvement scores but not initial intelligibility. On the other hand, receptive vocabulary scores predicted initial intelligibility scores but not intelligibility improvement. Expertise in rhythm perception appears to provide an advantage for processing dysrhythmic speech, but a familiarization experience is required for the advantage to be realized. Findings are discussed in relation to the role of rhythm in speech processing and shed light on processing models that consider the consequence of rhythm abnormalities in dysarthria.

Artificial intelligence: Learning to see and act

NASA Astrophysics Data System (ADS)

Schölkopf, Bernhard

2015-02-01

An artificial-intelligence system uses machine learning from massive training sets to teach itself to play 49 classic computer games, demonstrating that it can adapt to a variety of tasks. See Letter p.529

What Are Intellectual and Developmental Disabilities (IDDs)?

MedlinePlus

... characterized by problems with both: Intellectual functioning or intelligence, which include the ability to learn, reason, problem ... cord, and nervous system function, which can affect intelligence and learning. These conditions can also cause other ...

Convergent evolution of complex brains and high intelligence

PubMed Central

Roth, Gerhard

2015-01-01

Within the animal kingdom, complex brains and high intelligence have evolved several to many times independently, e.g. among ecdysozoans in some groups of insects (e.g. blattoid, dipteran, hymenopteran taxa), among lophotrochozoans in octopodid molluscs, among vertebrates in teleosts (e.g. cichlids), corvid and psittacid birds, and cetaceans, elephants and primates. High levels of intelligence are invariantly bound to multimodal centres such as the mushroom bodies in insects, the vertical lobe in octopodids, the pallium in birds and the cerebral cortex in primates, all of which contain highly ordered associative neuronal networks. The driving forces for high intelligence may vary among the mentioned taxa, e.g. needs for spatial learning and foraging strategies in insects and cephalopods, for social learning in cichlids, instrumental learning and spatial orientation in birds and social as well as instrumental learning in primates. PMID:26554042

The Learning Organisation Part II. "Getting Emotional": The Learning Organisation and Emotional Intelligence. CLMS Working Paper.

ERIC Educational Resources Information Center

Hughes, Jason

Emotional intelligence (EI) can be a diagnostic tool and a set of guiding principals to address the learning organization's concern of overcoming the barriers to collective learning. EI can be defined as "how well you handle yourself." It refers to "emotional literacy" and a person's capacity to manage emotions and use them as…

What We Call Smart: A New Narrative for Intelligence and Learning. School-Age Children Series.

ERIC Educational Resources Information Center

Miller, Lynda

Noting that the collective stories of special education have grown out of a tradition that, by its nature tends to perpetuate problems, this book examines such narratives and how they influence thinking and belief about intelligence and learning. It begins by examining how the current story of intelligence developed and illustrates some of the…

Does Learning to Read Improve Intelligence? A Longitudinal Multivariate Analysis in Identical Twins from Age 7 to 16

ERIC Educational Resources Information Center

Ritchie, Stuart J.; Bates, Timothy C.; Plomin, Robert

2015-01-01

Evidence from twin studies points to substantial environmental influences on intelligence, but the specifics of this influence are unclear. This study examined one developmental process that potentially causes intelligence differences: learning to read. In 1,890 twin pairs tested at 7, 9, 10, 12, and 16 years, a cross-lagged…

The Relationship between Emotional Intelligence and Middle School Students with Learning Disabilities

ERIC Educational Resources Information Center

Petersen, Vanessa C.

2010-01-01

The purpose of the present study was to investigate the relationship between emotional intelligence and academic success in middle school students with learning disabilities. Emotional Intelligence (EI) was measured using the BarOn Emotional Quotient Inventory: Youth Version (BarOn EQ-i: YV). The results of the BarOn EQ-i: YV was then compared to…

Long-Term Stability of Scores on the Wechsler Intelligence Scale for Children-Fourth Edition in Children with Learning Disabilities

ERIC Educational Resources Information Center

Lander, Jenny

2010-01-01

The present investigation explored the stability of scores on the Wechsler Intelligence Scale for Children-IV (WISC-IV) over approximately a three-year period. Previous research has suggested that some children with Learning Disabilities (LD) do not demonstrate long-term stability of intelligence. Legally, school districts are no longer required…

Information gathering, management and transferring for geospatial intelligence - A conceptual approach to create a spatial data infrastructure

NASA Astrophysics Data System (ADS)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-06-01

Since long ago, information is a key factor for military organizations. In military context the success of joint and combined operations depends on the accurate information and knowledge flow concerning the operational theatre: provision of resources, environment evolution, targets' location, where and when an event will occur. Modern military operations cannot be conceive without maps and geospatial information. Staffs and forces on the field request large volume of information during the planning and execution process, horizontal and vertical geospatial information integration is critical for decision cycle. Information and knowledge management are fundamental to clarify an environment full of uncertainty. Geospatial information (GI) management rises as a branch of information and knowledge management, responsible for the conversion process from raw data collect by human or electronic sensors to knowledge. Geospatial information and intelligence systems allow us to integrate all other forms of intelligence and act as a main platform to process and display geospatial-time referenced events. Combining explicit knowledge with person know-how to generate a continuous learning cycle that supports real time decisions, mitigates the influences of fog of war and provides the knowledge supremacy. This paper presents the analysis done after applying a questionnaire and interviews about the GI and intelligence management in a military organization. The study intended to identify the stakeholder's requirements for a military spatial data infrastructure as well as the requirements for a future software system development.

What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

PubMed

Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

2016-07-01

We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Into the field: naturalistic education and the future of conservation.

PubMed

Hayes, Mark A

2009-10-01

Some educational psychologists and researchers have argued that there are multiple ways of being intelligent. In the early 1980s, Howard Gardner presented a theory of multiple intelligences by proposing that humans can be described not by a single kind of intelligence, or intelligence quotient score, but rather by a variety of kinds of intelligence. This idea of considering multiple views of intelligence has helped educators look at intelligence from a less rigid, more expansive perspective. I considered how the relatively new concept of naturalistic intelligence, which is the cognitive potential to process information that is exhibited by expert naturalists, might influence the design of undergraduate biology curricula. Naturalistic intelligence can be fostered in undergraduate biology students by emphasizing the need for well-rounded scientific naturalists; developing curricula that involves students in outdoor inquiry-based projects; and helping students learn how to observe both the natural world and their own learning, skills that are essential to developing expert naturalistic knowledge. Professors, graduate students, and administrators can improve the naturalistic intelligence of undergraduate biology students by giving these students opportunities to be involved in outdoor research. Time spent outdoors alone and among people with expertise in natural history, ecology, and conservation biology will have important influences on the knowledge and skills biology undergraduates learn, the careers they pursue, and the contributions they make to conserving Earth's biodiversity.

Supervisory Control and Data Acquisition (SCADA) Security Awareness In a Resource Constrained Learning Environment

DTIC Science & Technology

2014-06-16

SCADA systems. These professionals should be aware of the vulnerabilities so they can take intelligent precautions to mitigate attacks. SCADA...vulnerabilities • Describe mitigation options for protecting a system from SCADA attacks For students that go on to pursue a degree in Computer...from SCADA attacks For students who do not remain in the IT realm, this introduction provides an awareness to help them mitigate threats for their

Covariation of learning and "reasoning" abilities in mice: evolutionary conservation of the operations of intelligence.

PubMed

Wass, Christopher; Denman-Brice, Alexander; Rios, Chris; Light, Kenneth R; Kolata, Stefan; Smith, Andrew M; Matzel, Louis D

2012-04-01

Contemporary descriptions of human intelligence hold that this trait influences a broad range of cognitive abilities, including learning, attention, and reasoning. Like humans, individual genetically heterogeneous mice express a "general" cognitive trait that influences performance across a diverse array of learning and attentional tasks, and it has been suggested that this trait is qualitatively and structurally analogous to general intelligence in humans. However, the hallmark of human intelligence is the ability to use various forms of "reasoning" to support solutions to novel problems. Here, we find that genetically heterogeneous mice are capable of solving problems that are nominally indicative of inductive and deductive forms of reasoning, and that individuals' capacity for reasoning covaries with more general learning abilities. Mice were characterized for their general learning ability as determined by their aggregate performance (derived from principal component analysis) across a battery of five diverse learning tasks. These animals were then assessed on prototypic tests indicative of deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping") and inductive reasoning (execution of an efficient search strategy in a binary decision tree). The animals exhibited systematic abilities on each of these nominal reasoning tasks that were predicted by their aggregate performance on the battery of learning tasks. These results suggest that the coregulation of reasoning and general learning performance in genetically heterogeneous mice form a core cognitive trait that is analogous to human intelligence. (c) 2012 APA, all rights reserved.

Enhancing Language Teaching and Learning by Keeping Individual Differences in Perspective

ERIC Educational Resources Information Center

Sulaiman, Suriati; Sulaiman, Tajularipin

2010-01-01

Learners differ from each other in many ways particularly in cognitive abilities. These factors eventually affect their learning abilities. Thus teachers should look into learner differences in intelligence before designing a teaching and learning program for them. Gardner proposed a much broader view of the definition of intelligence than a…

Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

ERIC Educational Resources Information Center

Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

2017-01-01

Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

A Conversational Intelligent Tutoring System to Automatically Predict Learning Styles

ERIC Educational Resources Information Center

Latham, Annabel; Crockett, Keeley; McLean, David; Edmonds, Bruce

2012-01-01

This paper proposes a generic methodology and architecture for developing a novel conversational intelligent tutoring system (CITS) called Oscar that leads a tutoring conversation and dynamically predicts and adapts to a student's learning style. Oscar aims to mimic a human tutor by implicitly modelling the learning style during tutoring, and…

Impact of Learned Resourcefulness and Theories of Intelligence on Academic Achievement of University Students: An Integrated Approach

ERIC Educational Resources Information Center

Kennett, Deborah J.; Keefer, Kateryna

2006-01-01

This was the first study to integrate Rosenbaum's concept of learned resourcefulness with Dweck's implicit theories of intelligence in predicting university students' academic self-control behaviour and year-end grades. Rosenbaum highlights the prominent role that learned resourcefulness skills play in promoting mastery responses and goal…

Contributions of Associative Learning to Age and Individual Differences in Fluid Intelligence

ERIC Educational Resources Information Center

Tamez, Elaine; Myerson, Joel; Hale, Sandra

2012-01-01

According to the cognitive cascade hypothesis, age-related slowing results in decreased working memory, which in turn affects higher-order cognition. Because recent studies show complex associative learning correlates highly with fluid intelligence, the present study examined the role of complex associative learning in cognitive cascade models of…

Identifying Students' Characteristic Learning Behaviors in an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam

2012-01-01

Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…

Perceptions of the use of intelligent information access systems in university level active learning activities among teachers of biomedical subjects.

PubMed

Aparicio, Fernando; Morales-Botello, María Luz; Rubio, Margarita; Hernando, Asunción; Muñoz, Rafael; López-Fernández, Hugo; Glez-Peña, Daniel; Fdez-Riverola, Florentino; de la Villa, Manuel; Maña, Manuel; Gachet, Diego; Buenaga, Manuel de

2018-04-01

Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emerging disciplines such as 'educational data mining' and 'learning analytics and knowledge' have provided clear examples of the importance of the use of artificial intelligence techniques in education. The main objective of this study was to gather expert opinions regarding the benefits of using complementary methods that are supported by intelligent systems, specifically, by intelligent information access systems, when processing texts written in natural language and the benefits of using these methods as companion tools to the learning activities that are employed by biomedical and health sciences teachers. Eleven teachers of degree courses who belonged to the Faculties of Biomedical Sciences (BS) and Health Sciences (HS) of a Spanish university in Madrid were individually interviewed. These interviews were conducted using a mixed methods questionnaire that included 66 predefined close-ended and open-ended questions. In our study, three intelligent information access systems (i.e., BioAnnote, CLEiM and MedCMap) were successfully used to evaluate the teacher's perceptions regarding the utility of these systems and their different methods in learning activities. All teachers reported using active learning methods in the classroom, most of which were computer programs that were used for initially designing and later executing learning activities. All teachers used case-based learning methods in the classroom, with a specific emphasis on case reports written in Spanish and/or English. In general, few or none of the teachers were familiar with the technical terms related to the technologies used for these activities such as "intelligent systems" or "concept/mental maps". However, they clearly realized the potential applicability of such approaches in both the preparation and the effective use of these activities in the classroom. Specifically, the themes highlighted by a greater number of teachers after analyzing the responses to the open-ended questions were the usefulness of BioAnnote system to provide reliable sources of medical information and the usefulness of the bilingual nature of CLEiM system for learning medical terminology in English. Three intelligent information access systems were successfully used to evaluate the teacher's perceptions regarding the utility of these systems in learning activities. The results of this study showed that integration of reliable sources of information, bilingualism and selective annotation of concepts were the most valued features by the teachers, who also considered the incorporation of these systems into learning activities to be potentially very useful. In addition, in the context of our experimental conditions, our work provides useful insights into the way to appropriately integrate this type of intelligent information access systems into learning activities, revealing key themes to consider when developing such approaches. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Open Ambient Intelligence Environments.

PubMed

Burzagli, Laura; Emiliani, Pier Luigi

2015-01-01

The present impact of ambient intelligence concepts in eInclusion is first briefly reviewed. Suggestions and examples of how ambient intelligent environments should be specified, designed and used to favour independent living of people with activity limitations are presented.

Integrating Multiple Intelligences and Learning Styles on Solving Problems, Achievement in, and Attitudes towards Math in Six Graders with Learning Disabilities in Cooperative Groups

ERIC Educational Resources Information Center

Eissa, Mourad Ali; Mostafa, Amaal Ahmed

2013-01-01

This study investigated the effect of using differentiated instruction by integrating multiple intelligences and learning styles on solving problems, achievement in, and attitudes towards math in six graders with learning disabilities in cooperative groups. A total of 60 students identified with LD were invited to participate. The sample was…

A Game Based e-Learning System to Teach Artificial Intelligence in the Computer Sciences Degree

ERIC Educational Resources Information Center

de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel

2017-01-01

Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…

E-Learning, Multiple Intelligences Theory (MI) and Learner-Centred Instruction: Adapting MI Learning Theoretical Principles to the Instruction of Health and Safety to Construction Managers

ERIC Educational Resources Information Center

McNamee, Paul; Madden, Dave; McNamee, Frank; Wall, John; Hurst, Alan; Vrasidas, Charalambos; Chanquoy, Lucile; Baccino, Thierry; Acar, Emrah; Onwy-Yazici, Ela; Jordan, Ann

2009-01-01

This paper describes an ongoing EU project concerned with developing an instructional design framework for virtual classes (VC) that is based on the theory of Multiple Intelligences (MI) (1983). The psychological theory of Multiple Intelligences (Gardner 1983) has received much credence within instructional design since its inception and has been…

The Relationship between Iranian EFL High School Students' Multiple Intelligence Scores and Their Use of Learning Strategies

ERIC Educational Resources Information Center

Hajhashemi, Karim; Ghombavani, Fatemeh Parasteh; Amirkhiz, Seyed Yasin Yazdi

2011-01-01

According to the theory of multiple intelligences (MI) propounded by Gardner (1983, 1999a, 1999b), each individual has a multitude of intelligences that are quite independent of each other and each individual has a unique cognitive profile. Having access to the MI profiles and learning strategies of learners could help the teachers in planning…

Individual Differences in Learning and Cognitive Abilities

DTIC Science & Technology

1989-09-15

conducted by Sir Francis Galton . Galton’s view of intelligence was that it distinguished those individuals who had genius (e.g., demonstrated by making...genius must have more refined sensory and motor faculties. Thus, Galton argued, intelligence could be measured by assessing constructs such as visual...block number) FIELD GROUP SUB-GROUP Learning, individual differences, cognitive abilities, 05 09 intelligence , skill acquisition, perceptual speed, - i

Weaving Whole Cloth: The Nurture of a Highly Intelligent Child. What Is It Like To Live with a Highly Intelligent Child?

ERIC Educational Resources Information Center

Sargeant, Hope

2000-01-01

The parent of an extremely intelligent child discusses what it is like to live with a child who exhibits a different web of cognition, perception, intuition, and mental processing; the necessity of educational acceleration for learning to achieve and develop self-esteem; and the importance of challenging material in learning the satisfaction of…

Artificial Intelligence-Based Student Learning Evaluation: A Concept Map-Based Approach for Analyzing a Student's Understanding of a Topic

ERIC Educational Resources Information Center

Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D.

2014-01-01

In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…

Fixed Point Learning Based Intelligent Traffic Control System

NASA Astrophysics Data System (ADS)

Zongyao, Wang; Cong, Sui; Cheng, Shao

2017-10-01

Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

The Concept Mastery in the Perspective of Gender of Junior High School Students on Eclipse Theme in Multiple Intelligences-based of Integrated Earth and Space Science Learning

NASA Astrophysics Data System (ADS)

Liliawati, W.; Utama, J. A.; Mursydah, L. S.

2017-03-01

The purpose of this study is to identify gender-based concept mastery differences of junior high school students after the implementation of multiple intelligences-based integrated earth and space science learning. Pretest-posttest group design was employed to two different classes at one of junior high school on eclipse theme in Tasikmalaya West Java: one class for boys (14 students) and one class of girls (18 students). The two-class received same treatment. The instrument of concepts mastery used in this study was open-ended eight essay questions. Reliability test result of this instrument was 0.9 (category: high) while for validity test results were high and very high category. We used instruments of multiple intelligences identification and learning activity observation sheet for our analysis. The results showed that normalized N-gain of concept mastery for boys and girls were improved, respectively 0.39 and 0.65. Concept mastery for both classes differs significantly. The dominant multiple intelligences for boys were in kinesthetic while girls dominated in the rest of multiple intelligences. Therefor we concluded that the concept mastery was influenced by gender and student’s multiple intelligences. Based on this finding we suggested to considering the factor of gender and students’ multiple intelligences given in the learning activity.

Implementation of multiple intelligences theory in the English language course syllabus at the University of Nis Medical School.

PubMed

Bakić-Mirić, Natasa

2010-01-01

Theory of multiple intelligences (MI) is considered an innovation in learning the English language because it helps students develop all eight intelligences that, on the other hand, represent ways people understand the world around them, solve problems and learn. They are: verbal/linguistic, logical/mathematical, visual/spatial, bodily/kinaesthetic, musical/rhythmic, interpersonal, intrapersonal and naturalist. Also, by focusing on the problem-solving activities, teachers, by implementing theory of multiple intelligences, encourage students not only to build their existing language knowledge but also learn new content and skills. The objective of this study has been to determine the importance of implementation of the theory of multiple intelligences in the English language course syllabus at the University of Nis Medical School. Ways in which the theory of multiple intelligences has been implemented in the English language course syllabus particularly in one lecture for junior year students of pharmacy in the University of Nis Medical School. The English language final exam results from February 2009 when compared with the final exam results from June 2007 prior to the implementation of MI theory showed the following: out of 80 junior year students of pharmacy, 40 obtained grade 10 (outstanding), 16 obtained grade 9 (excellent), 11 obtained grade 8 (very good), 4 obtained grade 7 (good) and 9 obtained grade 6 (pass). No student failed. The implementation of the theory of multiple intelligences in the English language course syllabus at the University of Nis Medical School has had a positive impact on learning the English language and has increased students' interest in language learning. Genarally speaking, this theory offers better understanding of students' intelligence and greater appreciation of their strengths. It provides numerous opportunities for students to use and develop all eight intelligences not just the few they excel in prior to enrolling in a university or college.

Cognitive differences between orang-utan species: a test of the cultural intelligence hypothesis

PubMed Central

Forss, Sofia I. F.; Willems, Erik; Call, Josep; van Schaik, Carel P.

2016-01-01

Cultural species can - or even prefer to - learn their skills from conspecifics. According to the cultural intelligence hypothesis, selection on underlying mechanisms not only improves this social learning ability but also the asocial (individual) learning ability. Thus, species with systematically richer opportunities to socially acquire knowledge and skills should over time evolve to become more intelligent. We experimentally compared the problem-solving ability of Sumatran orang-utans (Pongo abelii), which are sociable in the wild, with that of the closely related, but more solitary Bornean orang-utans (P. pygmaeus), under the homogeneous environmental conditions provided by zoos. Our results revealed that Sumatrans showed superior innate problem-solving skills to Borneans, and also showed greater inhibition and a more cautious and less rough exploration style. This pattern is consistent with the cultural intelligence hypothesis, which predicts that the more sociable of two sister species experienced stronger selection on cognitive mechanisms underlying learning. PMID:27466052

Cognitive differences between orang-utan species: a test of the cultural intelligence hypothesis.

PubMed

Forss, Sofia I F; Willems, Erik; Call, Josep; van Schaik, Carel P

2016-07-28

Cultural species can - or even prefer to - learn their skills from conspecifics. According to the cultural intelligence hypothesis, selection on underlying mechanisms not only improves this social learning ability but also the asocial (individual) learning ability. Thus, species with systematically richer opportunities to socially acquire knowledge and skills should over time evolve to become more intelligent. We experimentally compared the problem-solving ability of Sumatran orang-utans (Pongo abelii), which are sociable in the wild, with that of the closely related, but more solitary Bornean orang-utans (P. pygmaeus), under the homogeneous environmental conditions provided by zoos. Our results revealed that Sumatrans showed superior innate problem-solving skills to Borneans, and also showed greater inhibition and a more cautious and less rough exploration style. This pattern is consistent with the cultural intelligence hypothesis, which predicts that the more sociable of two sister species experienced stronger selection on cognitive mechanisms underlying learning.

Convergent evolution of complex brains and high intelligence.

PubMed

Roth, Gerhard

2015-12-19

Within the animal kingdom, complex brains and high intelligence have evolved several to many times independently, e.g. among ecdysozoans in some groups of insects (e.g. blattoid, dipteran, hymenopteran taxa), among lophotrochozoans in octopodid molluscs, among vertebrates in teleosts (e.g. cichlids), corvid and psittacid birds, and cetaceans, elephants and primates. High levels of intelligence are invariantly bound to multimodal centres such as the mushroom bodies in insects, the vertical lobe in octopodids, the pallium in birds and the cerebral cortex in primates, all of which contain highly ordered associative neuronal networks. The driving forces for high intelligence may vary among the mentioned taxa, e.g. needs for spatial learning and foraging strategies in insects and cephalopods, for social learning in cichlids, instrumental learning and spatial orientation in birds and social as well as instrumental learning in primates. © 2015 The Author(s).

Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

NASA Astrophysics Data System (ADS)

Ibrahim, Wael Refaat Anis

The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an alarm is instigated predicting the advent of system abnormal operation. The incoming data could be compared to previous trends as well as matched to trends developed through computer simulations and stored using fuzzy learning.

STEM-based science learning implementation to identify student’s personal intelligences profiles

NASA Astrophysics Data System (ADS)

Wiguna, B. J. P. K.; Suwarma, I. R.; Liliawati, W.

2018-05-01

Science and technology are rapidly developing needs to be balanced with the human resources that have the qualified ability. Not only cognitive ability, but also have the soft skills that support 21st century skills. Science, Technology, Engineering, and Mathematics (STEM) Education is a solution to improve the quality of learning and prepare students may be able to trained 21st century skills. This study aims to analyse the implementation of STEM-based science learning on Newton’s law of motion by identifying the personal intelligences profile junior high school students. The method used in this research is pre experiment with the design of the study one group pre-test post-test. Samples in this study were 26 junior high school students taken using Convenience Sampling. Students personal intelligences profile after learning STEM-based science uses two instruments, self-assessment and peer assessment. Intrapersonal intelligence profile based self-assessment and peer assessment are respectively 69.38; and 64.08. As for interpersonal intelligence for self-assessment instrument is 73 and the peer assessment is 60.23.

Intelligently interactive combat simulation

NASA Astrophysics Data System (ADS)

Fogel, Lawrence J.; Porto, Vincent W.; Alexander, Steven M.

2001-09-01

To be fully effective, combat simulation must include an intelligently interactive enemy... one that can be calibrated. But human operated combat simulations are uncalibratable, for we learn during the engagement, there's no average enemy, and we cannot replicate their culture/personality. Rule-based combat simulations (expert systems) are not interactive. They do not take advantage of unexpected mistakes, learn, innovate, and reflect the changing mission/situation. And it is presumed that the enemy does not have a copy of the rules, that the available experts are good enough, that they know why they did what they did, that their combat experience provides a sufficient sample and that we know how to combine the rules offered by differing experts. Indeed, expert systems become increasingly complex, costly to develop, and brittle. They have face validity but may be misleading. In contrast, intelligently interactive combat simulation is purpose- driven. Each player is given a well-defined mission, reference to the available weapons/platforms, their dynamics, and the sensed environment. Optimal tactics are discovered online and in real-time by simulating phenotypic evolution in fast time. The initial behaviors are generated randomly or include hints. The process then learns without instruction. The Valuated State Space Approach provides a convenient way to represent any purpose/mission. Evolutionary programming searches the domain of possible tactics in a highly efficient manner. Coupled together, these provide a basis for cruise missile mission planning, and for driving tank warfare simulation. This approach is now being explored to benefit Air Force simulations by a shell that can enhance the original simulation.

Dataset of two experiments of the application of gamified peer assessment model into online learning environment MeuTutor.

PubMed

Tenório, Thyago; Bittencourt, Ig Ibert; Isotani, Seiji; Pedro, Alan; Ospina, Patrícia; Tenório, Daniel

2017-06-01

In this dataset, we present the collected data of two experiments with the application of the gamified peer assessment model into online learning environment MeuTutor to allow the comparison of the obtained results with others proposed models. MeuTutor is an intelligent tutoring system aims to monitor the learning of the students in a personalized way, ensuring quality education and improving the performance of its members (Tenório et al., 2016) [1]. The first experiment evaluated the effectiveness of the peer assessment model through metrics as final grade (result), time to correct the activities and associated costs. The second experiment evaluated the gamification influence into peer assessment model, analyzing metrics as access number (logins), number of performed activities and number of performed corrections. In this article, we present in table form for each metric: the raw data of each treatment; the summarized data; the application results of the normality test Shapiro-Wilk; the application results of the statistical tests T -Test and/or Wilcoxon. The presented data in this article are related to the article entitled "A gamified peer assessment model for on-line learning environments in a competitive context" (Tenório et al., 2016) [1].

Biologically inspired computation and learning in Sensorimotor Systems

NASA Astrophysics Data System (ADS)

Lee, Daniel D.; Seung, H. S.

2001-11-01

Networking systems presently lack the ability to intelligently process the rich multimedia content of the data traffic they carry. Endowing artificial systems with the ability to adapt to changing conditions requires algorithms that can rapidly learn from examples. We demonstrate the application of such learning algorithms on an inexpensive quadruped robot constructed to perform simple sensorimotor tasks. The robot learns to track a particular object by discovering the salient visual and auditory cues unique to that object. The system uses a convolutional neural network that automatically combines color, luminance, motion, and auditory information. The weights of the networks are adjusted using feedback from a teacher to reflect the reliability of the various input channels in the surrounding environment. Additionally, the robot is able to compensate for its own motion by adapting the parameters of a vestibular ocular reflex system.

Home environment, nutritional status and maternal intelligence as determinants of intellectual development in rural Philippine preschool children.

PubMed

Church, A T; Katigbak, M S

1991-01-01

Psychologists used 7 subtests based on Western intelligence tests but developed for rural preschoolers in Tagalog-speaking regions of the Philippines to estimate intelligence of 177 5-6 year old children in 4 agricultural villages in the provinces of Batangas and Oriental Mindoro. They also assessed the height for age, weight for age, and mid upper arm circumference of the children to determine nutritional status. They used 2 subtests from the Philippine Aptitude Classification Test to estimate the intelligence of 181 mothers and asked the mothers questions from the Environmental Interview Questionnaire to determine the status of the home environment. The psychologists hoped to examine the association between home environment, nutritional status, and intellectual development in these preschool children. A moderate association existed between home environment and intellectual development. It contributed more to child intellectual performance than did socioeconomic status and maternal intelligence. The physical and psychosocial environment also contributed to intellectual development. Maternal intelligence, a partial index of genetic influence, could not altogether explain the association between home environment and intellectual development. These results may identify environment experiences concerning environmental specificity such as exploration of the surrounding environment and spatial ability. Intellectual development was not significantly related to nutritional status in normal to moderately malnourished children.

"Lessons learned" : evaluation of intelligent transportation systems (ITS) implementation at Santee Wateree Regional Transportation Authority.

DOT National Transportation Integrated Search

2002-06-01

The purpose of this lessons learned is to document the experience with Intelligent Transportation Systems (ITS) : implementation at the Santee Wateree Regional Transportation authority (SWRTA). SWRTA is a public : transportation provider servin...

Survey on Intelligent Assistance for Workplace Learning in Software Engineering

NASA Astrophysics Data System (ADS)

Ras, Eric; Rech, Jörg

Technology-enhanced learning (TEL) systems and intelligent assistance systems aim at supporting software engineers during learning and work. A questionnaire-based survey with 89 responses from industry was conducted to find out what kinds of services should be provided and how, as well as to determine which software engineering phases they should focus on. In this paper, we present the survey results regarding intelligent assistance for workplace learning in software engineering. We analyzed whether specific types of assistance depend on the organization's size, the respondent's role, and the experience level. The results show a demand for TEL that supports short-term problem solving and long-term competence development at the workplace.

Clustering and Profiling Students According to Their Interactions with an Intelligent Tutoring System Fostering Self-Regulated Learning

ERIC Educational Resources Information Center

Bouchet, Francois; Harley, Jason M.; Trevors, Gregory J.; Azevedo, Roger

2013-01-01

In this paper, we present the results obtained using a clustering algorithm (Expectation-Maximization) on data collected from 106 college students learning about the circulatory system with MetaTutor, an agent-based Intelligent Tutoring System (ITS) designed to foster self-regulated learning (SRL). The three extracted clusters were validated and…

Analysis of Students' Online Learning Readiness Based on Their Emotional Intelligence Level

ERIC Educational Resources Information Center

Engin, Melih

2017-01-01

The objective of the present study is to determine whether there is a significant relationship between the students' readiness in online learning and their emotional intelligence levels. Correlational research method was used in the study. Online Learning Readiness Scale which was developed by Hung et al. (2010) has been used and Trait Emotional…

Improved Modeling of Intelligent Tutoring Systems Using Ant Colony Optimization

ERIC Educational Resources Information Center

Rastegarmoghadam, Mahin; Ziarati, Koorush

2017-01-01

Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…

Using a Problem-Based Learning Approach to Teach an Intelligent Systems Course

ERIC Educational Resources Information Center

Cheong, France

2008-01-01

While delivering the Intelligent Systems course, an elective course in the Master of Business Information Technology program at RMIT University, it was felt that there was a learning issue as students' learning seemed to be superficial. This perception was based on the questions students asked in class and the mechanical attitude they adopted…

Correlations between the Stanford-Binet, 4th Edition, and the WISC-R with a Learning Disabled Population.

ERIC Educational Resources Information Center

Phelps, LeAdelle; And Others

1988-01-01

Compared Stanford-Binet (Fourth Edition) and the Wechsler Intelligence Scale for Children-Revised as instruments for assessing the intellectual strengths and weaknesses of students (N=35) classified as learning disabled in elementary and secondary grades. Results suggest the tests will yield similar intelligence quotients for the learning disabled…

Errors and Intelligence in Computer-Assisted Language Learning: Parsers and Pedagogues. Routledge Studies in Computer Assisted Language Learning

ERIC Educational Resources Information Center

Heift, Trude; Schulze, Mathias

2012-01-01

This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate…

Substructure Discovery of Macro-Operators

DTIC Science & Technology

1988-05-01

Aspects of Scientific Discovery," in Machine Learning: An Artifcial Intelligence Approach, Vol. II. R. S. Michalski, J. G. Carbonell and T. M. Mitchell (ed... intelligent robot using this system could learn how to perform new tasks by watching tasks being performed by someone else. even if the robot does not possess...Substructure Discovery of Macro-Operators* Bradley L. Whitehall Artificial Intelligence Research Group Coordinated Science Laboratory ’University of Illinois at

A Correlational Study of the Relationships between Implicit Theories of Intelligence, Perceived Self-Efficacy, Self-Regulated Learning, and Academic Achievement of Undergraduate Students at an HBCU

ERIC Educational Resources Information Center

Spicer, Margaret I.

2017-01-01

The purpose of this study was to explore possible relationships between the implicit theories of intelligence, self-efficacy, self-regulated learning, and academic achievement of undergraduate students enrolled at an HBCU in a mid-Atlantic state. Three instruments were used in this study: (a) the Implicit Theory of Intelligence Scale (TOI), (b)…

Multiple intelligences and alternative teaching strategies: The effects on student academic achievement, conceptual understanding, and attitude

NASA Astrophysics Data System (ADS)

Baragona, Michelle

The purpose of this study was to investigate the interactions between multiple intelligence strengths and alternative teaching methods on student academic achievement, conceptual understanding and attitudes. The design was a quasi-experimental study, in which students enrolled in Principles of Anatomy and Physiology, a developmental biology course, received lecture only, problem-based learning with lecture, or peer teaching with lecture. These students completed the Multiple Intelligence Inventory to determine their intelligence strengths, the Students' Motivation Toward Science Learning questionnaire to determine student attitudes towards learning in science, multiple choice tests to determine academic achievement, and open-ended questions to determine conceptual understanding. Effects of intelligence types and teaching methods on academic achievement and conceptual understanding were determined statistically by repeated measures ANOVAs. No significance occurred in academic achievement scores due to lab group or due to teaching method used; however, significant interactions between group and teaching method did occur in students with strengths in logical-mathematical, interpersonal, kinesthetic, and intrapersonal intelligences. Post-hoc analysis using Tukey HSD tests revealed students with strengths in logical-mathematical intelligence and enrolled in Group Three scored significantly higher when taught by problem-based learning (PBL) as compared to peer teaching (PT). No significance occurred in conceptual understanding scores due to lab group or due to teaching method used; however, significant interactions between group and teaching method did occur in students with strengths in musical, kinesthetic, intrapersonal, and spatial intelligences. Post-hoc analysis using Tukey HSD tests revealed students with strengths in logical-mathematical intelligence and enrolled in Group Three scored significantly higher when taught by lecture as compared to PBL. Students with strengths in intrapersonal intelligence and enrolled in Group One scored significantly lower when taught by lecture as compared to PBL. Results of a repeated measures ANOVA for student attitudes showed significant increases in positive student attitudes toward science learning for all three types of teaching method between pretest and posttest; but there were no significant differences in posttest attitude scores by type of teaching method.

Intelligent Tutor

NASA Technical Reports Server (NTRS)

1990-01-01

NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.

Brave New World of Intelligence Testing.

ERIC Educational Resources Information Center

Rice, Berkeley

1979-01-01

New approaches to assessing intelligence are discussed, as well as new intelligence tests. Among the developments are investigating neurometrics, adapting testing to the effects of technology on children, countering cultural bias, assessing social intelligence, focusing on aspects of cognitive styles, measuring learning potential, and using…

Artificial Intelligence--Applications in Education.

ERIC Educational Resources Information Center

Poirot, James L.; Norris, Cathleen A.

1987-01-01

This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…

The relationship between intelligence and training gains is moderated by training strategy.

PubMed

Lee, Hyunkyu; Boot, Walter R; Baniqued, Pauline L; Voss, Michelle W; Prakash, Ruchika Shaurya; Basak, Chandramallika; Kramer, Arthur F

2015-01-01

We examined the relationship between training regimen and fluid intelligence in the learning of a complex video game. Fifty non-game-playing young adults were trained on a game called Space Fortress for 30 hours with one of two training regimens: (1) Hybrid Variable-Priority Training (HVT), with part-task training and a focus on improving specific skills and managing task priorities, and (2) Full Emphasis Training (FET) in which participants practiced the whole game to obtain the highest overall score. Fluid intelligence was measured with the Raven's Progressive Matrix task before training. With FET, fluid intelligence was positively associated with learning, suggesting that intellectual ability played a substantial role in determining individual differences in training success. In contrast, with HVT, fluid intelligence was not associated with learning, suggesting that individual differences in fluid intelligence do not factor into training success in a regimen that emphasizes component tasks and flexible task coordination. By analyzing training effects in terms of individual differences and training regimens, the current study offers a training approach that minimizes the potentially limiting effect of individual differences.

Effects of cross-language voice training on speech perception: Whose familiar voices are more intelligible?

PubMed Central

Levi, Susannah V.; Winters, Stephen J.; Pisoni, David B.

2011-01-01

Previous research has shown that familiarity with a talker’s voice can improve linguistic processing (herein, “Familiar Talker Advantage”), but this benefit is constrained by the context in which the talker’s voice is familiar. The current study examined how familiarity affects intelligibility by manipulating the type of talker information available to listeners. One group of listeners learned to identify bilingual talkers’ voices from English words, where they learned language-specific talker information. A second group of listeners learned the same talkers from German words, and thus only learned language-independent talker information. After voice training, both groups of listeners completed a word recognition task with English words produced by both familiar and unfamiliar talkers. Results revealed that English-trained listeners perceived more phonemes correct for familiar than unfamiliar talkers, while German-trained listeners did not show improved intelligibility for familiar talkers. The absence of a processing advantage in speech intelligibility for the German-trained listeners demonstrates limitations on the Familiar Talker Advantage, which crucially depends on the language context in which the talkers’ voices were learned; knowledge of how a talker produces linguistically relevant contrasts in a particular language is necessary to increase speech intelligibility for words produced by familiar talkers. PMID:22225059

Artificial intelligence approaches for rational drug design and discovery.

PubMed

Duch, Włodzisław; Swaminathan, Karthikeyan; Meller, Jarosław

2007-01-01

Pattern recognition, machine learning and artificial intelligence approaches play an increasingly important role in rational drug design, screening and identification of candidate molecules and studies on quantitative structure-activity relationships (QSAR). In this review, we present an overview of basic concepts and methodology in the fields of machine learning and artificial intelligence (AI). An emphasis is put on methods that enable an intuitive interpretation of the results and facilitate gaining an insight into the structure of the problem at hand. We also discuss representative applications of AI methods to docking, screening and QSAR studies. The growing trend to integrate computational and experimental efforts in that regard and some future developments are discussed. In addition, we comment on a broader role of machine learning and artificial intelligence approaches in biomedical research.

Enhancing Collaborative Learning through Group Intelligence Software

NASA Astrophysics Data System (ADS)

Tan, Yin Leng; Macaulay, Linda A.

Employers increasingly demand not only academic excellence from graduates but also excellent interpersonal skills and the ability to work collaboratively in teams. This paper discusses the role of Group Intelligence software in helping to develop these higher order skills in the context of an enquiry based learning (EBL) project. The software supports teams in generating ideas, categorizing, prioritizing, voting and multi-criteria decision making and automatically generates a report of each team session. Students worked in a Group Intelligence lab designed to support both face to face and computer-mediated communication and employers provided feedback at two key points in the year long team project. Evaluation of the effectiveness of Group Intelligence software in collaborative learning was based on five key concepts of creativity, participation, productivity, engagement and understanding.

Toward Augmented Radiologists: Changes in Radiology Education in the Era of Machine Learning and Artificial Intelligence.

PubMed

Tajmir, Shahein H; Alkasab, Tarik K

2018-06-01

Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools, how they can help them improve their practice, and be able to effectively supervise their use. Radiology training programs will need to develop curricula to help trainees acquire the knowledge to carry out this new supervisory duty of radiologists. In the longer term, artificially intelligent software assistants could have a transformative effect on the training of residents and fellows, and offer new opportunities to bring learning into the ongoing practice of attending radiologists. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

A New Deep Learning Model for Fault Diagnosis with Good Anti-Noise and Domain Adaptation Ability on Raw Vibration Signals

PubMed Central

Zhang, Wei; Peng, Gaoliang; Li, Chuanhao; Chen, Yuanhang; Zhang, Zhujun

2017-01-01

Intelligent fault diagnosis techniques have replaced time-consuming and unreliable human analysis, increasing the efficiency of fault diagnosis. Deep learning models can improve the accuracy of intelligent fault diagnosis with the help of their multilayer nonlinear mapping ability. This paper proposes a novel method named Deep Convolutional Neural Networks with Wide First-layer Kernels (WDCNN). The proposed method uses raw vibration signals as input (data augmentation is used to generate more inputs), and uses the wide kernels in the first convolutional layer for extracting features and suppressing high frequency noise. Small convolutional kernels in the preceding layers are used for multilayer nonlinear mapping. AdaBN is implemented to improve the domain adaptation ability of the model. The proposed model addresses the problem that currently, the accuracy of CNN applied to fault diagnosis is not very high. WDCNN can not only achieve 100% classification accuracy on normal signals, but also outperform the state-of-the-art DNN model which is based on frequency features under different working load and noisy environment conditions. PMID:28241451

Semiosis in self-producing systems

NASA Astrophysics Data System (ADS)

Sharov, Alexei

2000-05-01

Cybernetic methodology has reached its limits in the study of life because it ignores the meaning of biological information. Thus it should be augmented by semiotics that studies the meaning and value of signs. According to the pragmatic definition, a sign is a biological adaptation, i.e. a persistent useful function. Usefulness of an action can be measured by its contribution to the reproductive value of an organism in a particular quasi-species. Reproductive values are equal to the components of the left eigenvector of the linearized model of system dynamics. Every organism is a sign, and its life cycle is a continuous process of self-interpretation. Organisms use receptors to predict changing environments. Natural selection is functionally equivalent to perception at the level of lineages. Selective survival and reproduction is analogous to selective excitation of photoreceptors in the eye. Lineages learn how to avoid harmful variation by using developmental constraints, proofreading, dominance, and other mechanisms. If intelligence is defined as the ability to learn, then lineages are intelligent systems, which we did not recognize simply because they are too slow.

Psychobiology of the amniotic environment.

PubMed

Benassi, Luigi; Accorsi, Francesca; Marconi, Lorenza; Benassi, Gianluca

2004-01-01

Water, basic element of amniotic fluid (A.F.), is closely related to Life, Fertility and Motherhood in several cultures and religions. Through material evidences of an essential growth medium and useful diagnostic source, a new concept grow up: the fluid as a first real environment in which fetus lives and acts. Many studies confirm that in A.F. fetus starts his character-building, his memory and his intelligence. The fluid seems to be the first means of learning and acknowledgement. Sounds, smells and tastes are perceived as well as emotions and fears. Urinoterapy and staminal cells sampling shows how A.F. can be considered as an additional terapeutic resource.

Learning about leadership - A personal account.

PubMed

Cheang, P P

2011-01-01

A personal account of learning about leadership. This article introduces the theory of power and influence, and aimed to report especially the personal reflection, emotional intelligence and learning about oneself that occurred on the way. Reading, group discussion and active reflection. Thoughts, reflections and learning were recorded regularly. The concept of leadership, influence tactics and emotional intelligence all have implications in workplace relationship management and ultimately leadership qualities. The issues discussed serves as food for thought for others. This is a genuine and very personal learning experience.

Toward an embedded training tool for Deep Space Network operations

NASA Technical Reports Server (NTRS)

Hill, Randall W., Jr.; Sturdevant, Kathryn F.; Johnson, W. L.

1993-01-01

There are three issues to consider when building an embedded training system for a task domain involving the operation of complex equipment: (1) how skill is acquired in the task domain; (2) how the training system should be designed to assist in the acquisition of the skill, and more specifically, how an intelligent tutor could aid in learning; and (3) whether it is feasible to incorporate the resulting training system into the operational environment. This paper describes how these issues have been addressed in a prototype training system that was developed for operations in NASA's Deep Space Network (DSN). The first two issues were addressed by building an executable cognitive model of problem solving and skill acquisition of the task domain and then using the model to design an intelligent tutor. The cognitive model was developed in Soar for the DSN's Link Monitor and Control (LMC) system; it led to several insights about learning in the task domain that were used to design an intelligent tutor called REACT that implements a method called 'impasse-driven tutoring'. REACT is one component of the LMC training system, which also includes a communications link simulator and a graphical user interface. A pilot study of the LMC training system indicates that REACT shows promise as an effective way for helping operators to quickly acquire expert skills.

Teaching About "Brain and Learning" in High School Biology Classes: Effects on Teachers' Knowledge and Students' Theory of Intelligence.

PubMed

Dekker, Sanne; Jolles, Jelle

2015-01-01

This study evaluated a new teaching module about "Brain and Learning" using a controlled design. The module was implemented in high school biology classes and comprised three lessons: (1) brain processes underlying learning; (2) neuropsychological development during adolescence; and (3) lifestyle factors that influence learning performance. Participants were 32 biology teachers who were interested in "Brain and Learning" and 1241 students in grades 8-9. Teachers' knowledge and students' beliefs about learning potential were examined using online questionnaires. Results indicated that before intervention, biology teachers were significantly less familiar with how the brain functions and develops than with its structure and with basic neuroscientific concepts (46 vs. 75% correct answers). After intervention, teachers' knowledge of "Brain and Learning" had significantly increased (64%), and more students believed that intelligence is malleable (incremental theory). This emphasizes the potential value of a short teaching module, both for improving biology teachers' insights into "Brain and Learning," and for changing students' beliefs about intelligence.

Toward Agent Programs with Circuit Semantics

NASA Technical Reports Server (NTRS)

Nilsson, Nils J.

1992-01-01

New ideas are presented for computing and organizing actions for autonomous agents in dynamic environments-environments in which the agent's current situation cannot always be accurately discerned and in which the effects of actions cannot always be reliably predicted. The notion of 'circuit semantics' for programs based on 'teleo-reactive trees' is introduced. Program execution builds a combinational circuit which receives sensory inputs and controls actions. These formalisms embody a high degree of inherent conditionality and thus yield programs that are suitably reactive to their environments. At the same time, the actions computed by the programs are guided by the overall goals of the agent. The paper also speculates about how programs using these ideas could be automatically generated by artificial intelligence planning systems and adapted by learning methods.

Digging deeper on "deep" learning: A computational ecology approach.

PubMed

Buscema, Massimo; Sacco, Pier Luigi

2017-01-01

We propose an alternative approach to "deep" learning that is based on computational ecologies of structurally diverse artificial neural networks, and on dynamic associative memory responses to stimuli. Rather than focusing on massive computation of many different examples of a single situation, we opt for model-based learning and adaptive flexibility. Cross-fertilization of learning processes across multiple domains is the fundamental feature of human intelligence that must inform "new" artificial intelligence.

Facts and fiction of learning systems. [decision making intelligent control

NASA Technical Reports Server (NTRS)

Saridis, G. N.

1975-01-01

The methodology that will provide the updated precision for the hardware control and the advanced decision making and planning in the software control is called learning systems and intelligent control. It was developed theoretically as an alternative for the nonsystematic heuristic approaches of artificial intelligence experiments and the inflexible formulation of modern optimal control methods. Its basic concepts are discussed and some feasibility studies of some practical applications are presented.

Learning to Solve Problems by Searching for Macro-Operators

DTIC Science & Technology

1983-07-01

executing generalized robot plans. Aritificial Intelligence 3:25 1-288, 1972. [Frey 821 Frey, Alexander Ii. Jr., and David Singmaster. Handbook of Cubik...and that searching for macros may be a useful general learning paradigm. 1.1. Introduction One view of die die field of artificial intelligence is that... intelligence literature [Schofield 67, Gaschnig 79, Ericsson 761 and provides one of the simplest examples of the operation of the Macro Problem Solver. It

Intelligence and Changes in Regional Cerebral Glucose Metabolic Rate Following Learning.

ERIC Educational Resources Information Center

Haier, Richard J.; And Others

1992-01-01

A study of eight normal right-handed men demonstrates widespread significant decreases in brain glucose metabolic rate (GMR) following learning a complex computer task, a computer game. Correlations between magnitude of GMR change and intelligence scores are also demonstrated. (SLD)

Help Helps, but Only so Much: Research on Help Seeking with Intelligent Tutoring Systems

ERIC Educational Resources Information Center

Aleven, Vincent; Roll, Ido; McLaren, Bruce M.; Koedinger, Kenneth R.

2016-01-01

Help seeking is an important process in self-regulated learning (SRL). It may influence learning with intelligent tutoring systems (ITSs), because many ITSs provide help, often at the student's request. The Help Tutor was a tutor agent that gave in-context, real-time feedback on students' help-seeking behavior, as they were learning with an ITS.…

Emotional and Meta-Emotional Intelligence as Predictors of Adjustment Problems in Students with Specific Learning Disorders

ERIC Educational Resources Information Center

D'Amico, Antonella; Guastaferro, Teresa

2017-01-01

The purpose of this study was to analyse adjustment problems in a group of adolescents with a Specific Learning Disorder (SLD), examining to what extent they depend on the severity level of the learning disorder and/or on the individual's level of emotional intelligence. Adjustment problems,, perceived severity levels of SLD, and emotional and…

Measuring Learning Potential: An Alternative to the Traditional Intelligence Test. Studies in Learning Potential, Volume 3, Number 39.

ERIC Educational Resources Information Center

Budoff, Milton

Proposed is the assessment of learning potential through a test-train-retest paradigm in addition to the traditional intelligence test with mentally handicapped or disadvantaged children. Discussed is a rationale for the approach which posits that poor and/or nonwhite children do not have equal access to school-preparatory experiences though they…

Emotional intelligence as a predictor of academic performance in first-year accelerated graduate entry nursing students.

PubMed

Fernandez, Ritin; Salamonson, Yenna; Griffiths, Rhonda

2012-12-01

To examine the association between trait emotional intelligence and learning strategies and their influence on academic performance among first-year accelerated nursing students. The study used a prospective survey design. A sample size of 81 students (100% response rate) who undertook the accelerated nursing course at a large university in Sydney participated in the study. Emotional intelligence was measured using the adapted version of the 144-item Trait Emotional Intelligence Questionnaire. Four subscales of the Motivated Strategies for Learning Questionnaire were used to measure extrinsic goal motivation, peer learning, help seeking and critical thinking among the students. The grade point average score obtained at the end of six months was used to measure academic achievement. The results demonstrated a statistically significant correlation between emotional intelligence scores and critical thinking (r = 0.41; p < 0.001), help seeking (r = 0.33; p < 0.003) and peer learning (r = 0.32; p < 0.004) but not with extrinsic goal orientation (r = -0.05; p < 0.677). Emotional intelligence emerged as a significant predictor of academic achievement (β = 0.25; p = 0.023). In addition to their learning styles, higher levels of awareness and understanding of their own emotions have a positive impact on students' academic achievement. Higher emotional intelligence may lead students to pursue their interests more vigorously and think more expansively about subjects of interest, which could be an explanatory factor for higher academic performance in this group of nursing students. The concepts of emotional intelligence are central to clinical practice as nurses need to know how to deal with their own emotions as well as provide emotional support to patients and their families. It is therefore essential that these skills are developed among student nurses to enhance the quality of their clinical practice. © 2012 Blackwell Publishing Ltd.

The Speech Intelligibility Index and the pure-tone average as predictors of lexical ability in children fit with hearing AIDS.

PubMed

Stiles, Derek J; Bentler, Ruth A; McGregor, Karla K

2012-06-01

To determine whether a clinically obtainable measure of audibility, the aided Speech Intelligibility Index (SII; American National Standards Institute, 2007), is more sensitive than the pure-tone average (PTA) at predicting the lexical abilities of children who wear hearing aids (CHA). School-age CHA and age-matched children with normal hearing (CNH) repeated words and nonwords, learned novel words, and completed a standardized receptive vocabulary test. Analyses of covariance allowed comparison of the 2 groups. For CHA, regression analyses determined whether SII held predictive value over and beyond PTA. CHA demonstrated poorer performance than CNH on tests of word and nonword repetition and receptive vocabulary. Groups did not differ on word learning. Aided SII was a stronger predictor of word and nonword repetition and receptive vocabulary than PTA. After accounting for PTA, aided SII remained a significant predictor of nonword repetition and receptive vocabulary. Despite wearing hearing aids, CHA performed more poorly on 3 of 4 lexical measures. Individual differences among CHA were predicted by aided SII. Unlike PTA, aided SII incorporates hearing aid amplification characteristics and speech-frequency weightings and may provide a more valid estimate of the child's access to and ability to learn from auditory input in real-world environments.

Theories of Intelligence: Background and Measures.

ERIC Educational Resources Information Center

Dweck, Carol S.; Henderson, Valanne L.

Research on implicit beliefs or theories about intelligence has shown that those with entity theories tend to be oriented toward performance goals--that is, toward documenting their intelligence, while those with incremental theories tend to be oriented toward learning goals--that is, toward developing their intelligence. This paper discusses…

Learning and Teaching through the Naturalist Intelligence.

ERIC Educational Resources Information Center

Meyer, Maggie

1998-01-01

Howard Gardner defines naturalists as persons who recognize flora and fauna and other consequential distinctions in the natural world and use this ability productively. A sixth-grade teacher discusses Gardner's theory of multiple intelligences, specifically the naturalist intelligence, and suggests ways to teach the naturalist intelligence through…

Speech Intelligibility of Aircrew Mask Communication Configurations in High-Noise Environments

DTIC Science & Technology

2017-09-28

ARL-TR-8168 ● Sep 2017 US Army Research Laboratory Speech Intelligibility of Aircrew Mask Communication Configurations in High ...Laboratory Speech Intelligibility of Aircrew Mask Communication Configurations in High -Noise Environments by Kimberly A Pollard and Lamar Garrett...in High - Noise Environments 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Kimberly A Pollard and Lamar

Attention control learning in the decision space using state estimation

NASA Astrophysics Data System (ADS)

Gharaee, Zahra; Fatehi, Alireza; Mirian, Maryam S.; Nili Ahmadabadi, Majid

2016-05-01

The main goal of this paper is modelling attention while using it in efficient path planning of mobile robots. The key challenge in concurrently aiming these two goals is how to make an optimal, or near-optimal, decision in spite of time and processing power limitations, which inherently exist in a typical multi-sensor real-world robotic application. To efficiently recognise the environment under these two limitations, attention of an intelligent agent is controlled by employing the reinforcement learning framework. We propose an estimation method using estimated mixture-of-experts task and attention learning in perceptual space. An agent learns how to employ its sensory resources, and when to stop observing, by estimating its perceptual space. In this paper, static estimation of the state space in a learning task problem, which is examined in the WebotsTM simulator, is performed. Simulation results show that a robot learns how to achieve an optimal policy with a controlled cost by estimating the state space instead of continually updating sensory information.

Intelligent Learning System using cognitive science theory and artificial intelligence methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cristensen, D.L.

1986-01-01

This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic ismore » used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.« less

Lessons learned in the development of the STOL intelligent tutoring system

NASA Technical Reports Server (NTRS)

Seamster, Thomas; Baker, Clifford; Ames, Troy

1991-01-01

Lessons learned during the development of the NASA Systems Test and Operations Language (STOL) Intelligent Tutoring System (ITS), being developed at NASA Goddard Space Flight Center are presented. The purpose of the intelligent tutor is to train STOL users by adapting tutoring based on inferred student strengths and weaknesses. This system has been under development for over one year and numerous lessons learned have emerged. These observations are presented in three sections, as follows. The first section addresses the methodology employed in the development of the STOL ITS and briefly presents the ITS architecture. The second presents lessons learned, in the areas of: intelligent tutor development; documentation and reporting; cost and schedule control; and tools and shells effectiveness. The third section presents recommendations which may be considered by other ITS developers, addressing: access, use and selection of subject matter experts; steps involved in ITS development; use of ITS interface design prototypes as part of knowledge engineering; and tools and shells effectiveness.

Future applications of artificial intelligence to Mission Control Centers

NASA Technical Reports Server (NTRS)

Friedland, Peter

1991-01-01

Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

Effective e-learning for health professional and medical students: the experience with SIAS-Intelligent Tutoring System.

PubMed

Muñoz, Diana C; Ortiz, Alexandra; González, Carolina; López, Diego M; Blobel, Bernd

2010-01-01

Current e-learning systems are still inadequate to support the level of interaction, personalization and engagement demanded by clinicians, care givers, and the patient themselves. For effective e-learning to be delivered in the health context, collaboration between pedagogy and technology is required. Furthermore, e-learning systems should be flexible enough to be adapted to the students' needs, evaluated regularly, easy to use and maintain and provide students' feedback, guidelines and supporting material in different formats. This paper presents the implementation of an Intelligent Tutoring System (SIAS-ITS), and its evaluation compared to a traditional virtual learning platform (Moodle). The evaluation was carried out as a case study, in which the participants were separated in two groups, each group attending a virtual course on the WHO Integrated Management of Childhood Illness (IMCI) strategy supported by one of the two e-learning platforms. The evaluation demonstrated that the participants' knowledge level, pedagogical strategies used, learning efficiency and systems' usability were improved using the Intelligent Tutoring System.

How Computers Are Used in the Teaching of Music and Speculations about How Artificial Intelligence Could Be Applied to Radically Improve the Learning of Compositional Skills. CITE Report No. 6.

ERIC Educational Resources Information Center

Holland, Simon

This paper forms part of a preliminary survey for work on the application of artificial intelligence theories and techniques to the learning of music composition skills. The paper deals with present day applications of computers to the teaching of music and speculations about how artificial intelligence might be used to foster music composition in…

The evolution of primate general and cultural intelligence

PubMed Central

Reader, Simon M.; Hager, Yfke; Laland, Kevin N.

2011-01-01

There are consistent individual differences in human intelligence, attributable to a single ‘general intelligence’ factor, g. The evolutionary basis of g and its links to social learning and culture remain controversial. Conflicting hypotheses regard primate cognition as divided into specialized, independently evolving modules versus a single general process. To assess how processes underlying culture relate to one another and other cognitive capacities, we compiled ecologically relevant cognitive measures from multiple domains, namely reported incidences of behavioural innovation, social learning, tool use, extractive foraging and tactical deception, in 62 primate species. All exhibited strong positive associations in principal component and factor analyses, after statistically controlling for multiple potential confounds. This highly correlated composite of cognitive traits suggests social, technical and ecological abilities have coevolved in primates, indicative of an across-species general intelligence that includes elements of cultural intelligence. Our composite species-level measure of general intelligence, ‘primate gS’, covaried with both brain volume and captive learning performance measures. Our findings question the independence of cognitive traits and do not support ‘massive modularity’ in primate cognition, nor an exclusively social model of primate intelligence. High general intelligence has independently evolved at least four times, with convergent evolution in capuchins, baboons, macaques and great apes. PMID:21357224

Intelligence, Cognition, and Language of Green Plants.

PubMed

Trewavas, Anthony

2016-01-01

A summary definition of some 70 descriptions of intelligence provides a definition for all other organisms including plants that stresses fitness. Barbara McClintock, a plant biologist, posed the notion of the 'thoughtful cell' in her Nobel prize address. The systems structure necessary for a thoughtful cell is revealed by comparison of the interactome and connectome. The plant root cap, a group of some 200 cells that act holistically in responding to numerous signals, likely possesses a similar systems structure agreeing with Darwin's description of acting like the brain of a lower organism. Intelligent behavior requires assessment of different choices and taking the beneficial one. Decisions are constantly required to optimize the plant phenotype to a dynamic environment and the cambium is the assessing tissue diverting more or removing resources from different shoot and root branches through manipulation of vascular elements. Environmental awareness likely indicates consciousness. Spontaneity in plant behavior, ability to count to five and error correction indicate intention. Volatile organic compounds are used as signals in plant interactions and being complex in composition may be the equivalent of language accounting for self and alien recognition by individual plants. Game theory describes competitive interactions. Interactive and intelligent outcomes emerge from application of various games between plants themselves and interactions with microbes. Behavior profiting from experience, another simple definition of intelligence, requires both learning and memory and is indicated in the priming of herbivory, disease and abiotic stresses.

Experiential Learning Using QlikView Business Intelligence Software

ERIC Educational Resources Information Center

Podeschi, R. J.

2015-01-01

This paper reports on the use of QlikView business intelligence software for use in a Business Intelligence (BI) course within an undergraduate information systems program. The course provides students with concepts related to data warehousing, data mining, visualizations, and software tools to provide business intelligence solutions for decision…

Schooling Built on the Multiple Intelligences

ERIC Educational Resources Information Center

Kunkel, Christine D.

2009-01-01

This article features a school built on multiple intelligences. As the first multiple intelligences school in the world, the Key Learning Community shapes its students' days to include significant time in the musical, spatial and bodily-kinesthetic intelligences, as well as the more traditional areas of logical-mathematical and linguistics. In…

The Automated Primate Research Laboratory (APRL)

NASA Technical Reports Server (NTRS)

Pace, N.; Smith, G. D.

1972-01-01

A description is given of a self-contained automated primate research laboratory to study the effects of weightlessness on subhuman primates. Physiological parameters such as hemodynamics, respiration, blood constituents, waste, and diet and nutrition are analyzed for abnormalities in the simulated space environment. The Southeast Asian pig-tailed monkey (Macaca nemistrina) was selected for the experiments owing to its relative intelligence and learning capacity. The objective of the program is to demonstrate the feasibility of a man-tended primate space flight experiment.

Intelligent system for topic survey in MEDLINE by keyword recommendation and learning text characteristics.

PubMed

Tanaka, M; Nakazono, S; Matsuno, H; Tsujimoto, H; Kitamura, Y; Miyano, S

2000-01-01

We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.

Intelligent Tutoring System: A Tool for Testing the Research Curiosities of Artificial Intelligence Researchers

ERIC Educational Resources Information Center

Yaratan, Huseyin

2003-01-01

An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…

A New Theoretical Perspective of Cognitive Abilities

ERIC Educational Resources Information Center

Lynch, Sharon A.; Warner, Laverne

2012-01-01

Defining intelligence is a puzzle that has challenged educators and researchers for years. More recently, professionals are acknowledging that individuals possess many facets of intelligence and that learning is a complex combination of genetic factors, environmental influences, and life experiences that affect learning in unique ways (Salvia,…

"Group Intelligence": An Active Learning Exploration of Diversity in Evolution

ERIC Educational Resources Information Center

Parsons, Christopher J.; Salaita, Meisa K.; Hughes, Catherine H.; Lynn, David G.; Fristoe, Adam; Fristoe, Ariel; Grover, Martha A.

2017-01-01

"Group Intelligence" is an active learning, inquiry-based activity that introduces prebiotic chemistry, emergent complexity, and diversity's importance to adaptability across scales. Students explore the molecular emergence of order and function through theatrical exercises and games. Through 20 min of audio instruction and a discussion…

Conversational Simulation in Computer-Assisted Language Learning: Potential and Reality.

ERIC Educational Resources Information Center

Coleman, D. Wells

1988-01-01

Addresses the potential of conversational simulations for computer-assisted language learning (CALL) and reasons why this potential is largely untapped. Topics discussed include artificial intelligence; microworlds; parsing; realism versus reality in computer software; intelligent tutoring systems; and criteria to clarify what kinds of CALL…

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB)

NASA Technical Reports Server (NTRS)

Bardina, Jorge; Rajkumar, T.

2003-01-01

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB) is a real-time web-based command and control, communication, and intelligent simulation environment of ground-vehicle, launch and range operation activities. ILRO-VTB consists of a variety of simulation models combined with commercial and indigenous software developments (NASA Ames). It creates a hybrid software/hardware environment suitable for testing various integrated control system components of launch and range. The dynamic interactions of the integrated simulated control systems are not well understood. Insight into such systems can only be achieved through simulation/emulation. For that reason, NASA has established a VTB where we can learn the actual control and dynamics of designs for future space programs, including testing and performance evaluation. The current implementation of the VTB simulates the operations of a sub-orbital vehicle of mission, control, ground-vehicle engineering, launch and range operations. The present development of the test bed simulates the operations of Space Shuttle Vehicle (SSV) at NASA Kennedy Space Center. The test bed supports a wide variety of shuttle missions with ancillary modeling capabilities like weather forecasting, lightning tracker, toxic gas dispersion model, debris dispersion model, telemetry, trajectory modeling, ground operations, payload models and etc. To achieve the simulations, all models are linked using Common Object Request Broker Architecture (CORBA). The test bed provides opportunities for government, universities, researchers and industries to do a real time of shuttle launch in cyber space.

Intelligent launch and range operations virtual testbed (ILRO-VTB)

NASA Astrophysics Data System (ADS)

Bardina, Jorge; Rajkumar, Thirumalainambi

2003-09-01

Intelligent Launch and Range Operations Virtual Test Bed (ILRO-VTB) is a real-time web-based command and control, communication, and intelligent simulation environment of ground-vehicle, launch and range operation activities. ILRO-VTB consists of a variety of simulation models combined with commercial and indigenous software developments (NASA Ames). It creates a hybrid software/hardware environment suitable for testing various integrated control system components of launch and range. The dynamic interactions of the integrated simulated control systems are not well understood. Insight into such systems can only be achieved through simulation/emulation. For that reason, NASA has established a VTB where we can learn the actual control and dynamics of designs for future space programs, including testing and performance evaluation. The current implementation of the VTB simulates the operations of a sub-orbital vehicle of mission, control, ground-vehicle engineering, launch and range operations. The present development of the test bed simulates the operations of Space Shuttle Vehicle (SSV) at NASA Kennedy Space Center. The test bed supports a wide variety of shuttle missions with ancillary modeling capabilities like weather forecasting, lightning tracker, toxic gas dispersion model, debris dispersion model, telemetry, trajectory modeling, ground operations, payload models and etc. To achieve the simulations, all models are linked using Common Object Request Broker Architecture (CORBA). The test bed provides opportunities for government, universities, researchers and industries to do a real time of shuttle launch in cyber space.

Intelligence and Cultural Environment, Methuen's Manuals of Modern Psychology Series.

ERIC Educational Resources Information Center

Vernon, Philip E.

This book describes recent psychological theories on the nature of intelligence and the influence of environmental factors, and argues that culture and child rearing practices affect the development of abilities (linguistic, sensory motor and perceptual). Studies of intelligence, achievement, and environment in England are discussed, along with…

Novel associative-memory-based self-learning neurocontrol model

NASA Astrophysics Data System (ADS)

Chen, Ke

1992-09-01

Intelligent control is an important field of AI application, which is closely related to machine learning, and the neurocontrol is a kind of intelligent control that controls actions of a physical system or a plant. Linear associative memory model is a good analytic tool for artificial neural networks. In this paper, we present a novel self-learning neurocontrol on the basis of the linear associative memory model to support intelligent control. Using our self-learning neurocontrol model, the learning process is viewed as an extension of one of J. Piaget's developmental stages. After a particular linear associative model developed by us is presented, a brief introduction to J. Piaget's cognitive theory is described as the basis of our self-learning style control. It follows that the neurocontrol model is presented, which usually includes two learning stages, viz. primary learning and high-level learning. As a demonstration of our neurocontrol model, an example is also presented with simulation techniques, called that `bird' catches an aim. The tentative experimental results show that the learning and controlling performance of this approach is surprisingly good. In conclusion, future research is pointed out to improve our self-learning neurocontrol model and explore other areas of application.

Closing the Mathematical Achievement Gap Through the Heart To the Brain: A Case Study of Urban High School Mathematics Teachers' Perceptions of How Their Emotional Intelligence Facilitates Instruction and Learning in the Classroom

NASA Astrophysics Data System (ADS)

Fang, Chung-Chieh

The purpose of this qualitative case study was to examine urban high school mathematics teachers' perceptions of how they manage their own and their students' emotional intelligence (EI) to facilitate instruction and learning; their reports of how they handle their emotions as urban mathematics teachers; and their reports of how they manage the emotions of their students. The study focused on the voices of sixteen urban mathematics teachers and was undertaken in reaction to the significant mathematics achievement gap between urban students and their suburban counterparts. The conceptual framework undergirding the study was synthesized work by Daniel Goleman, (1995) and Mayer and Salovey (1997); categorizing emotional intelligence in emotional selfawareness, managing emotions, harnessing emotions, empathy, and handling relationships. Research questions addressing each category were created and from these categories an interview guide was developed. Data gathered during individual teacher interviews was transcribed and sorted into emergent categories using open coding. The findings were organized and presented according to the study's research questions. Urban math teachers reported passion for their students, their feelings affect teaching and learning, and that humor is an important tool in mediating emotions. The study concludes with multiple recommendations for further research and practices. Future studies should compare teachers assuming paternal vs. mentor role when dealing with their students. The study can evaluate if either role has a significant impact in student teacher relationships. A recommendation for practice is for teachers to have professional development experiences focusing on the proper use of humor in the classroom. Humor used properly promotes a positive classroom environment. This is a skill that would be especially beneficial to urban teachers.

Architecture and biological applications of artificial neural networks: a tuberculosis perspective.

PubMed

Darsey, Jerry A; Griffin, William O; Joginipelli, Sravanthi; Melapu, Venkata Kiran

2015-01-01

Advancement of science and technology has prompted researchers to develop new intelligent systems that can solve a variety of problems such as pattern recognition, prediction, and optimization. The ability of the human brain to learn in a fashion that tolerates noise and error has attracted many researchers and provided the starting point for the development of artificial neural networks: the intelligent systems. Intelligent systems can acclimatize to the environment or data and can maximize the chances of success or improve the efficiency of a search. Due to massive parallelism with large numbers of interconnected processers and their ability to learn from the data, neural networks can solve a variety of challenging computational problems. Neural networks have the ability to derive meaning from complicated and imprecise data; they are used in detecting patterns, and trends that are too complex for humans, or other computer systems. Solutions to the toughest problems will not be found through one narrow specialization; therefore we need to combine interdisciplinary approaches to discover the solutions to a variety of problems. Many researchers in different disciplines such as medicine, bioinformatics, molecular biology, and pharmacology have successfully applied artificial neural networks. This chapter helps the reader in understanding the basics of artificial neural networks, their applications, and methodology; it also outlines the network learning process and architecture. We present a brief outline of the application of neural networks to medical diagnosis, drug discovery, gene identification, and protein structure prediction. We conclude with a summary of the results from our study on tuberculosis data using neural networks, in diagnosing active tuberculosis, and predicting chronic vs. infiltrative forms of tuberculosis.

WISC-R Types of Learning Disabilities: A Profile Analysis with Cross-Validation.

ERIC Educational Resources Information Center

Holcomb, William R.; And Others

1987-01-01

Profiles (Wechsler Intelligence Scale for Children - Revised) of 119 children in five learning disability programs were placed in six homogeneous groups using cluster analysis. One group showed superior intelligence quotient (IQ) with motor coordination deficits and severe emotional problems, while three groups represented children with low IQs…