Design of a multi-agent system using the "MaSE" method for learners' metacognitive help

This article addresses a multi-agent approach to solving the problem of integrating metacognitive incentives into Learning Management System. The behavior of the teacher in a classroom-teaching situation, where teacher adopting the competency-based approach, is characterized by a set of didactic interventions dynamically adaptable according to the actions-reactions of the learners. These interventions are continually subjected to perfection by experience. In this article, we are interested in modeling the multi-agent system in order to help the learners develop their metacognitive skills in a continuous way. The purpose of this system is to supervise the activities and statements of the learner and communicate them to the metacognitive agent. The latter focuses on the assessment of the learner's metacognitive skills in order to trigger, automatically, metacognitive incentives to provide help messages. Integrating the agent for metacognitive control and assistance, allows learners to maintain motivation and confidence, and elicit their attention to the importance of metacognitive skills during learning activity. The "MaSE" methodology and the "agentTool" are used to model the multi-agent system

Improving E-Learning by Integrating a Metacognitive Agent

The major disadvantage of the current Learning Management Systems is the lack of learner assistance in their learning processes and, therefore, they can not replace the presence of the teacher who ensures the progress of learning. In fact, we proposed to integrate, for each learner, a metacognitive agent that supported the metacognitive assistance and extracts the defectsin the learning process and strategies. The goal is to invite the learner to correct himself and improve his learning method. Metacognitive questionnaires were distributed to a group of 100 students before, during and after a computer course. The goal is to evaluatethe metacognitive attributes and to determine their influence on the success of learning. Decision trees were used as data analysis tools to extract a set of rules and to discover the influence of these metacognitive attributes on the result obtained by the learners. The results indicate that there are relationships between the different metacognitive attributes and the learners’ success. We note there is the influence of metacognitive incitement on learner outcomes, which reflects the degree of understanding of a learning pedagogical unit by the learner

Using a problem analysis model to enhance student learning in computer programming

Research on computer programming suggests that novice programmers possess inert knowledge when trying to solve programming problems. Moreover, research on teaching and learning computer programming indicates that offering appropriate conceptual models of computer programming concepts to novice programmers enhances their mental models and reduces their misconceptions in computer programming. The purpose of this study was to examine the effectiveness of a problem analysis learning model of computer programming to help novice programmers overcome their inert knowledge and learn a programming language;The problem analysis learning model combines a conceptual model and a holistic instructional approach for computer programming instruction. The conceptual component of the problem analysis model includes several computer simulations of database concepts. The purpose of the conceptual component of the problem analysis model is to offer students an opportunity to manipulate data in the computer simulations before formal instruction in order to help them construct their own knowledge of basic database concepts. The purpose of the holistic component of the problem analysis learning model is to help students integrate their programming knowledge to solve database problems. The holistic approach includes a four-step process that consists of problem introduction, problem diagnosis, learning activities, and database assignments;This study involved 100 inservice teachers enrolled in a basic computer programming workshop at The Institute for Secondary Schools Teachers in Taiwan (ISST). The teachers were randomly assigned to one of the two workshops conducted in this study (43 teachers in the control group and 53 teachers in the experimental group). Each workshop consisted of 36 hours of instruction over five days. Three subjects were taught in each workshop: basic computer concepts (BCC), Chinese word processing, and database activities;The results indicated that the problem analysis learning model helped the participants develop more complete mental models of basic database concepts. Moreover, the participants in the problem analysis learning model developed better database programming skills than those in the traditional computer programming workshop;The results of this study may provide a useful conceptual framework for the design of a computer programming course for teachers. Due to the results of this study, computer practitioners/teachers may re-organize their instructional methods used with existing content materials to enhance student learning in computer programming. Future researchers may use the problem analysis model as a foundation to explore learning in other subjects. Moreover, researchers could examine parts of this model in greater detail to identify specific items or procedures that contribute to student learning. Finally, this research study also provides a workshop structure to help inservice teachers increase their computing proficiency, and it may assist institutions in organizing their training programs

Deep Learning Approach for cognitive competency assessment in Computer Programming subject

This research examines the competencies that are essential for an lecturer or instructor to evaluate the student based on automated assessments. The competencies are the skills, knowledge, abilities and behavior that are required to perform the task given, whether in a learning or a working environment. The significance of this research is that it will assist students who are having difficulty learning a Computer Programming Language course to identify their flaws using a Deep Learning Approach. As a result, higher education institutions have a problem with assessing students based on their competency level because; they still use manual assessment to mark the assessment. In order to measure intelligence, it is necessary to identify the cluster of abilities or skills of the type in which intelligence expresses itself. This grouping of skills and abilities referred to as "competency". Then, an automated assessment is a problem-solving activity in which the student and the computer interact with no other human intervention. This review focuses on collecting different techniques that have been used. In addition, the review finding shows the main gap that exists within the context of the studied areas, which contributes to our key research topic of interest

Using metacognitive monitoring feedback to improve student learning in augmented reality environments

This research aims to use metacognitive monitoring feedback to improve student learning performance in an augmented reality environment. In this study, Microsoft HoloLens, a prominent augmented reality device and independent mobile computer, provided a more realistic augmented reality environment to engineering students. The near field electromagnetic ranging system collected students' real-time location data when they experienced the augmented reality learning modules. In Phase 1, the study utilized one of the topics in the Ergonomic class, called manual material handling. The Phase 1 experiment results showed that retrospective confidence judgments in augmented reality modules could significantly influence the way students learn when the contents require a high level of spatial awareness during content learning. Therefore, Phase 2 research considered specific engineering education related to spatial recognition. For Phase 2, the location-based augmented reality system was developed to improve user interaction. The augmented reality learning module was biomechanics: one of the Ergonomic class problematic concepts to engineering students. This new location-based augmented reality system allowed students to immerse themselves in the studying process and improved student engagement of hands-on training in an augmented reality environment. Metacognitive monitoring feedback was another tool applied to improve students' learning performance. Student test scores, confidence level, answering time, and reviewing time were collected as metrics for performance assessment during the experiment. Overall, Phases 1 and 2 study outcomes advanced our understanding of students' interactions and the learning content in an augmented reality learning environment. This study also provided a guideline for how engineers need to develop valuable learning content in augmented reality 'environments. Furthermore, using a metacognitive monitoring feedback tool in an augmented reality learning environment is an effective strategy to improve students' academic performance and calibration.Includes bibliographical references (pages 93-108)

Natural Language Tutoring and the Novice Programmer

For beginning programmers, inadequate problem solving and planning skills are among the most salient of their weaknesses. Novices, by definition, lack much of the tacit knowledge that underlies effective programming. This dissertation examines the efficacy of natural language tutoring (NLT) to foster acquisition of this tacit knowledge. Coached Program Planning (CPP) is proposed as a solution to the problem of teaching the tacit knowledge of programming. The general aim is to cultivate the development of such knowledge by eliciting and scaffolding the problem solving and planning activities that novices are known to underestimate or bypass altogether. ProPL (pro-PELL), a dialogue-based intelligent tutoring system based on CPP, is also described. In an evaluation, the primary findings were that students who received tutoring from ProPL seemed to exhibit an improved ability compose plans and displayed behaviors suggestive of thinking at greater levels of abstraction than students in a read-only control group. The major finding is that NLT appears to be effective in teaching program composition skills

Five Lenses on Team Tutor Challenges: A Multidisciplinary Approach

This chapter describes five disciplinary domains of research or lenses that contribute to the design of a team tutor. We focus on four significant challenges in developing Intelligent Team Tutoring Systems (ITTSs), and explore how the five lenses can offer guidance for these challenges. The four challenges arise in the design of team member interactions, performance metrics and skill development, feedback, and tutor authoring. The five lenses or research domains that we apply to these four challenges are Tutor Engineering, Learning Sciences, Science of Teams, Data Analyst, and Human–Computer Interaction. This matrix of applications from each perspective offers a framework to guide designers in creating ITTSs

Self-Directed Learning

This book on self-directed learning (SDL) is devoted to original academic scholarship within the field of education, and is the 6th volume in the North-West University (NWU) SDL book series. In this book the authors explore how self-directed learning can be considered an imperative for education in a complex modern society. Although each chapter represents independent research in the field of self-directed learning, the chapters form a coherent contribution concerning the scholarship of self-directed learning, and specifically the effect of environmental and praxis contexts on the enhancement of self-directed learning in a complex society. The publication as a whole provides diverse perspectives on the importance of self-directed learning in varied contexts. Scholars working in a wide range of fields are drawn together in this scholarly work to present a comprehensive dialogue regarding self-directed learning and how this concept functions in a complex and dynamic higher education context. This book presents a combination of theory and practice, which reflects selected conceptual dimensions of self-directed learning in society, as well as research-based findings pertaining to current topical issues relating to implementing self-directed learning in the modern world. The varied methodologies provide the reader with different and balanced perspectives, as well as varied and innovative ideas on how to conduct research in the field of self-directed learning

Self-Directed Learning

This book on self-directed learning (SDL) is devoted to original academic scholarship within the field of education, and is the 6th volume in the North-West University (NWU) SDL book series. In this book the authors explore how self-directed learning can be considered an imperative for education in a complex modern society. Although each chapter represents independent research in the field of self-directed learning, the chapters form a coherent contribution concerning the scholarship of self-directed learning, and specifically the effect of environmental and praxis contexts on the enhancement of self-directed learning in a complex society. The publication as a whole provides diverse perspectives on the importance of self-directed learning in varied contexts. Scholars working in a wide range of fields are drawn together in this scholarly work to present a comprehensive dialogue regarding self-directed learning and how this concept functions in a complex and dynamic higher education context. This book presents a combination of theory and practice, which reflects selected conceptual dimensions of self-directed learning in society, as well as research-based findings pertaining to current topical issues relating to implementing self-directed learning in the modern world. The varied methodologies provide the reader with different and balanced perspectives, as well as varied and innovative ideas on how to conduct research in the field of self-directed learning

Self-directed multimodal learning in higher education

This book aims to provide an overview of theoretical and practical considerations in terms of self-directed multimodal learning within the university context. Multimodal learning is approached in terms of the levels of multimodality and specifically blended learning and the mixing of modes of delivery (contact and distance education). As such, this publication will provide a unique snapshot of multimodal practices within higher education through a self-directed learning epistemological lens. The book covers issues such as what self-directed multimodal learning entails, mapping of specific publications regarding blended learning, blended learning in mathematics, geography, natural science and computer literacy, comparative experiences in distance education as well as situated and culturally appropriate learning in multimodal contexts. This book provides a unique focus on multimodality in terms of learning and delivery within the context of self-directed learning. Therefore, the publication would not only advance the scholarship of blended and open distance learning in South Africa, but also the contribute to enriching the discourse regarding self-direction. From this book readers will get an impression of the latest trends in literature in terms of multimodal self-directed learning in South Africa as well as unique empirical work being done in this regard