Modelling human teaching tactics and strategies for tutoring systems

One of the promises of ITSs and ILEs is that they will teach and assist learning in an intelligent manner. Historically this has tended to mean concentrating on the interface, on the representation of the domain and on the representation of the student’s knowledge. So systems have attempted to provide students with reifications both of what is to be learned and of the learning process, as well as optimally sequencing and adjusting activities, problems and feedback to best help them learn that domain. We now have embodied (and disembodied) teaching agents and computer-based peers, and the field demonstrates a much greater interest in metacognition and in collaborative activities and tools to support that collaboration. Nevertheless the issue of the teaching competence of ITSs and ILEs is still important, as well as the more specific question as to whether systems can and should mimic human teachers. Indeed increasing interest in embodied agents has thrown the spotlight back on how such agents should behave with respect to learners. In the mid 1980s Ohlsson and others offered critiques of ITSs and ILEs in terms of the limited range and adaptability of their teaching actions as compared to the wealth of tactics and strategies employed by human expert teachers. So are we in any better position in modelling teaching than we were in the 80s? Are these criticisms still as valid today as they were then? This paper reviews progress in understanding certain aspects of human expert teaching and in developing tutoring systems that implement those human teaching strategies and tactics. It concentrates particularly on how systems have dealt with student answers and how they have dealt with motivational issues, referring particularly to work carried out at Sussex: for example, on responding effectively to the student’s motivational state, on contingent and Vygotskian inspired teaching strategies and on the plausibility problem. This latter is concerned with whether tactics that are effectively applied by human teachers can be as effective when embodied in machine teachers

Integrating knowledge tracing and item response theory: A tale of two frameworks

Traditionally, the assessment and learning science commu-nities rely on different paradigms to model student performance. The assessment community uses Item Response Theory which allows modeling different student abilities and problem difficulties, while the learning science community uses Knowledge Tracing, which captures skill acquisition. These two paradigms are complementary - IRT cannot be used to model student learning, while Knowledge Tracing assumes all students and problems are the same. Recently, two highly related models based on a principled synthesis of IRT and Knowledge Tracing were introduced. However, these two models were evaluated on different data sets, using different evaluation metrics and with different ways of splitting the data into training and testing sets. In this paper we reconcile the models' results by presenting a unified view of the two models, and by evaluating the models under a common evaluation metric. We find that both models are equivalent and only differ in their training procedure. Our results show that the combined IRT and Knowledge Tracing models offer the best of assessment and learning sciences - high prediction accuracy like the IRT model, and the ability to model student learning like Knowledge Tracing

Motivational and metacognitive feedback in an ITS: linking past states and experiences to current problems

Feedback is an important element in learning as it can provide learners with both information about progress as well as external motivational stimuli, providing them with an opportunity for reflection. Motivation and metacognition are strongly intertwined, with learners high in self-efficacy more likely to use a variety of self-regulatory learning strategies, as well as to persist longer on challenging tasks. Learning from past experience involves metacognitive processes as an act of reflecting upon one’s own experience and, coupled with existing knowledge, aids the acquisition and construction of further knowledge. The aim of the research was to improve the learner’s focus on the process and experience of problem solving while using an Intelligent Tutoring System (ITS), by addressing the primary question: what are the effects of including motivational and metacognitive feedback based on the learner’s past states and experiences? An existing ITS, SQL-Tutor, was used in a study with participants from first year undergraduate degrees studying a database module. The study used two versions of SQL-Tutor: the Control group used a base version providing domain feedback and the Study group used an extended version that also provided motivational and metacognitive feedback. Three sources of data collection were used: module summative assessments, ITS log files and a post-study questionnaire. The analysis included both pre-post comparisons and how the participants interacted with the system, for example their persistence in problem-solving and the degree to which they referred to past learning. Comparisons between groups showed some differing trends both in learning and behaviour in favour of the Study group, though these trends were not significantly different. The study findings showed promise for the use of motivational and metacognitive feedback based on the learners’ past states and experiences that could be used as a basis for future research work and refinement

Learning from Recent British Information Literacy Models: A Report to ACRL\u27s Information Literacy Competency Standards for Higher Education Task Force

Information literacy is a fluid concept, shaped by our experiences, and changes in our information rich society. Guidelines articulating information literacy need modification to reflect the current form of this evolving concept. This report highlights the work of four groups in the United Kingdom to create innovative guidelines to assist practitioners in the promotion and teaching of information literacy

Modes and Mechanisms of Game-like Interventions in Intelligent Tutoring Systems

While games can be an innovative and a highly promising approach to education, creating effective educational games is a challenge. It requires effectively integrating educational content with game attributes and aligning cognitive and affective outcomes, which can be in conflict with each other. Intelligent Tutoring Systems (ITS), on the other hand, have proven to be effective learning environments that are conducive to strong learning outcomes. Direct comparisons between tutoring systems and educational games have found digital tutors to be more effective at producing learning gains. However, tutoring systems have had difficulties in maintaining students€™ interest and engagement for long periods of time, which limits their ability to generate learning in the long-term. Given the complementary benefits of games and digital tutors, there has been considerable effort to combine these two fields. This dissertation undertakes and analyzes three different ways of integrating Intelligent Tutoring Systems and digital games. We created three game-like systems with cognition, metacognition and affect as their primary target and mode of intervention. Monkey\u27s Revenge is a game-like math tutor that offers cognitive tutoring in a game-like environment. The Learning Dashboard is a game-like metacognitive support tool for students using Mathspring, an ITS. Mosaic comprises a series of mini-math games that pop-up within Mathspring to enhance students\u27 affect. The methodology consisted of multiple randomized controlled studies ran to evaluate each of these three interventions, attempting to understand their effect on students€™ performance, affect and perception of the intervention and the system that embeds it. Further, we used causal modeling to further explore mechanisms of action, the inter-relationships between student€™s incoming characteristics and predispositions, their mechanisms of interaction with the tutor, and the ultimate learning outcomes and perceptions of the learning experience

AI as a Methodology for Supporting Educational Praxis and Teacher Metacognition

Evidence-based practice (EBP) is of critical importance in education where emphasis is placed on the need to equip educators with an ability to independently generate and reflect on evidence of their practices in situ – a process also known as praxis. This paper examines existing research related to teachers’ metacognitive skills and, using two exemplar projects, it discusses the utility and relevance of AI methods of knowledge representation and knowledge elicitation as methodologies for supporting EBP. Research related to technology-enhanced communities of practice as a means for teachers to share and compare their knowledge with others is also examined. Suggestions for the key considerations in supporting teachers’ metacognition in praxis are made based on the review of literature and discussion of the specific projects, with the aim to highlight potential future research directions for AIEd. A proposal is made that a crucial part of AIEd’s future resides in its curating the role of AI as a methodology for supporting teacher training and continuous professional development, especially as relates to their developing metacognitive skills in relation to their practices

Clinical Reasoning in Physical Therapy: A Concept Analysis

Background Physical Therapy, along with most health professions, struggles to describe clinical reasoning, despite it being a vital skill in effective patient care. This lack of a unified conceptualization of clinical reasoning leads to variable and inconsistent teaching, assessment, and research. Objective The objective was to conceptualize a broad description of physical therapists’ clinical reasoning grounded in the published literature and to unify our understanding for future work related to teaching, assessment, and research. Design/Methods The design included a systematic concept analysis using Rodgers’ Evolutionary methodology. A concept analysis is a research methodology in which a concept\u27s characteristics and the relationship between features of the concept is clarified. Results Based on findings in the literature, clinical reasoning in physical therapy was conceptualized as integrating cognitive, psychomotor, and affective skills. It is contextual in nature and involves both therapist and client perspectives. It is adaptive, iterative, and collaborative with the intended outcome being a biopsychosocial approach to patient/client management. Limitations Although a comprehensive approach was intended, it is possible that the search methods or reduction of the literature was incomplete or key sources were mistakenly excluded. Conclusions A description of clinical reasoning in physical therapy was conceptualized, as it currently exists in representative literature. The intent is for it to contribute to the unification of an understanding of how clinical reasoning has been conceptualized to date by practitioners, academicians, and clinical educators. Substantial work remains to be done to further develop the concept of clinical reasoning for physical therapy, including the role of movement in our reasoning in practice

Metacognition in functional cognitive disorder

Functional cognitive disorder is common but underlying mechanisms remain poorly understood. Metacognition, an individual’s ability to reflect on and monitor cognitive processes, is likely to be relevant. Local metacognition refers to an ability to estimate confidence in cognitive performance on a moment-to-moment basis, whereas global metacognition refers to long-run self-evaluations of overall performance. Using a novel protocol comprising task-based measures and hierarchical Bayesian modelling, we compared local and global metacognitive performance in individuals with functional cognitive disorder. Eighteen participants with functional cognitive disorder (mean age = 49.2 years, 10 males) were recruited to this cross-sectional study. Participants completed computerized tasks that enabled local metacognitive efficiency for perception and memory to be measured using the hierarchical meta-d’ model within a signal detection theory framework. Participants also completed the Multifactorial Memory Questionnaire measuring global metacognition, and questionnaires measuring anxiety and depression. Estimates of local metacognitive efficiency were compared with those estimated from two control groups who had undergone comparable metacognitive tasks. Global metacognition scores were compared with the existing normative data. A hierarchical regression model was used to evaluate associations between global metacognition, depression and anxiety and local metacognitive efficiency, whilst simple linear regressions were used to evaluate whether affective symptomatology and local metacognitive confidence were associated with global metacognition. Participants with functional cognitive disorder had intact local metacognition for perception and memory when compared with controls, with the 95% highest density intervals for metacognitive efficiency overlapping with the two control groups in both cognitive domains. Functional cognitive disorder participants had significantly lower global metacognition scores compared with normative data; Multifactorial Memory Questionnaire-Ability subscale (t = 6.54, P < 0.0001) and Multifactorial Memory Questionnaire-Satisfaction subscale (t = 5.04, P < 0.0001). Mood scores, global metacognitive measures and metacognitive bias were not significantly associated with local metacognitive efficiency. Local metacognitive bias [β = −0.20 (SE = 0.09), q = 0.01] and higher depression scores as measured by the Patient Health Questionnaire-9 [β = −1.40 (SE = 2.56), q = 0.01] were associated with the lower global metacognition scores. We show that local metacognition is intact, whilst global metacognition is impaired, in functional cognitive disorder, suggesting a decoupling between the two metacognitive processes. In a Bayesian model, an aberrant prior (impaired global metacognition), may override bottom-up sensory input (intact local metacognition), giving rise to the subjective experience of abnormal cognitive processing. Future work should further investigate the interplay between local and global metacognition in functional cognitive disorder

Transactional Distance Theory: A Critical View of the Theoretical and Pedagogical Underpinnings of E-Learning

This chapter provides a critical look at the literature surrounding Distance Education and targets Transactional Distance Theory. It will examine in detail the three components: structure, interaction (or dialogue) and autonomy. The structure necessary for successful distance learning starts the chapter. Next, interaction (or dialogue) is introduced and the complexity of this in relation to the student experience is discussed. Finally, autonomy is explored in detail. This overview will relate specifically to the student perspective. Alternative approaches, links to seminal authors and a critical viewpoint is taken throughout