Advances in Intelligent Tutoring Systems: Problem-solving Modes and Model of Hints

Anohina, Alla

doi:10.15837/ijccc.2007.1.2336

Cited by 27 publications

(10 citation statements)

References 16 publications

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“…With the advent of a society based on technology and knowledge, focus has been put on having an ever-growing, highly skilled labour force [3] [9]. Learning institutions have been trying to adjust to these newly created needs by moving to a practice-oriented and more flexible type of education [9].…”

Section: Literature Reviewmentioning

confidence: 99%

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Incorporating a guided problem-solving method into ActiveMath using the House Model and logistic Regression

Pholo

Ngwira

2014

2014 IST-Africa Conference Proceedings

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In the past few decades, our world has changed from an industrial to an information society. This change has brought the need for a new set of skills in the workplace, including the ability to solve problems. Introducing technology in education is one response to this reform. Intelligent tutoring systems are one form of e-learning. They are designed to reasonably adapt to each learner or user based on their background and progressive achievement. Because of the various advantages of these systems attempts are made to incorporate problem solving skill impartation abilities for learners. This paper describes an adapted version of ActiveMath, which explicitly teaches problem solving to students using the House Model framework. Results show the technique does contribute to improve the problem solving skills of learners.

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Section: Literature Reviewmentioning

confidence: 99%

“…This change has affected various aspects of life, such as economy and education [1] [2]. The knowledge society has also had an impact on the professional world, which now requires higher-level skills from workers [1] [3].…”

Section: Introductionmentioning

confidence: 99%

Incorporating a guided problem-solving method into ActiveMath using the House Model and logistic Regression

Pholo

Ngwira

2014

2014 IST-Africa Conference Proceedings

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“…In spite of this, some systems have integrated mechanism clues during the problem solving to rely the students reasoning [3]. Therefore, this makes up an adaptive base, which depends on the apprentice's learning level.…”

Section: Related Workmentioning

confidence: 99%

“…For this, the inference machine makes the variable appear with the main screen, which has these three options associated with it. Later, the following rule is evaluated: 2,3,20,21,22,23,24,25, 26} SL This is a Reevaluation rule and has the function of making non-monotonic reasoning possible. Then, whenever the system executes the Div1 task, options 1, 2, 3 will be able to be evaluated again.…”

Section: B Implementation Of Knowledge Basementioning

confidence: 99%

An Artificial Intelligence Based Model for Algebra Education

Alonso-Lavernia

Barceló

2009

2009 Fifth International Joint Conference on INC, IMS and IDC

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Given the variety of operations that can be performed with monomials and polynomials, learning Algebra requires constant student training. Therefore, numerous solutions have been offered to resolve this problem, some with many possibilities for introducing content, others with an emphasis on practice, but very few with a follow-up of student activities. In the latter cases some statistical information of their interaction with the system is offered.This paper presents a comprehensive educational model for teaching Algebra, which includes, in addition to an educational system with wide opportunities for interaction with the student, a mechanism for generating dynamic exercises and a method of adaptive training based on records of student performance. These three features, with the possibility of emulating human behavior from knowledge-based systems, make this model an intelligent consulting tool for learning this subject.

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“…However, there is still a conspicuous absence of both rigorous evaluations and metacognitive interventions for learning in those developments. Solving of domain problems is important, but the mere solving is unlikely to lead to improved skills or deeper understanding of subject matter (Anohina, 2007). Learning often takes place best when the learner is actively involved in the cognitive processes of problem solving and receives feedback from the system on how to be more metacognitively adept.…”

Section: Introductionmentioning

confidence: 99%

The Effectiveness of an Adaptive Serious Game for Digital Logic Design

Tang¹,

Jahan²,

Bielefeldt³

2015 ASEE Annual Conference and Exposition Proceedings

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and developing pedagogical methods and materials to enhance engineering education. Her most recent educational research includes the collaboration with Tennessee State University and local high schools to infuse cyberinfrastructure learning experience into the pre-engineering and technology-based classrooms, the collaboration with community colleges to develop interactive games in empowering students with engineering literacy and problem-solving, the integration of system-on-chip concepts across two year Engineering Science and four year ECE curricula, and the implementation of an educational innovation that demonstrates science and engineering principles using an aquarium. Her work has resulted in over 100 journal and conference papers and book chapters. Dr. Kauser Jahan, Rowan UniversityKauser Jahan, is a Professor of Civil and Environmental Engineering at Rowan University. She received her B.S.C.E. from the Bangladesh University of Engineering and Technology, an MSCE from the University of Arkansas, Fayetteville and a Ph.D. from the University of Minnesota, Minneapolis. Her passion as an educator and mentor has been recognized by many professional organizations over the years. She is the recipient of the Gloucester County Women of Achievement Award, Lindback Foundation Teaching Award, the NJ ASCE Educator of the Year award, the Gary J. Hunter Excellence in Mentoring Award, the ASEE Environmental Engineering Division Meritorious Service Award, the ASEE Women in Engineering Division Sharon A. Keillor Award and the WEPAN Women in Engineering Initiative Award. She has been instrumental in establishing the Attracting Women into Engineering, the Engineers on Wheels and Engineering Clinics for Teachers programs at Rowan University. She has served as the Institutional Representative and Advisory Board Chair for the Women's Professional Network at Rowan University for six years and currently is an advisory board member of the New Jersey Chapter of the American Council on Education (ACE) Office of Women in Higher Education (OWHE). Mr. Talbot Bielefeldt, Clearwater Program EvaluationEducational program evaluator since 1995, working with a variety of federal, state, local, and corporate education initiatives. Current projects include evaluations of school/community and school/university grants focused on STEM education. The Effectiveness of An Adaptive Serious Game for Digital Logic Design ABSTRACTMost students benefit more deeply from guided learning than discovery learning. Even so, not all students are alike. Our research contention is that offering differentiated instructions that better fit students' educational needs in a narrative virtual reality (VR) environment will give them renewed hope for learning success. This paper presents such a development that augments an existing learning game, Gridlock, with an adaptive learning engine that assesses what really happens when a student's capacity is sabotaged in problem solving and to provide the help that is tailored to his/her needs. The game was deployed in Compute...

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Advances in Intelligent Tutoring Systems: Problem-solving Modes and Model of Hints

Cited by 27 publications

References 16 publications

Incorporating a guided problem-solving method into ActiveMath using the House Model and logistic Regression

Incorporating a guided problem-solving method into ActiveMath using the House Model and logistic Regression

An Artificial Intelligence Based Model for Algebra Education

The Effectiveness of an Adaptive Serious Game for Digital Logic Design

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