Issues in designing learning by teaching systems

Abstract: Learning by teaching systems are a relatively recent approach to designing Intelligent Learning Environments that place learners in the role of tutors. These systems are based on the practice of peer tutoring where students take on defined roles of tutor and tutee. An architecture for learning by teaching systems is described that does not require the domain model of an Intelligent Tutoring System. However a mutual communication language is needed and is defined by a conceptual syntax that delimits the domain content of the dialogue. An example learning by teaching system is described for the domain of qualitative economics. The construction and testing of this system inform a discussion of the major design issues involved: the nature of the learnt model, the form of the conceptual syntax, the control of the interaction and the possible introduction of domain knowledge. 1

Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis

In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments

From conditioning to learning communities: Implications of fifty years of research in e‐learning interaction design

This paper will consider e‐learning in terms of the underlying learning processes and interactions that are stimulated, supported or favoured by new media and the contexts or communities in which it is used. We will review and critique a selection of research and development from the past fifty years that has linked pedagogical and learning theory to the design of innovative e‐learning systems and activities, and discuss their implications. It will include approaches that are, essentially, behaviourist (Skinner and Gagné), cognitivist (Pask, Piaget and Papert), situated (Lave, Wenger and Seely‐Brown), socio‐constructivist (Vygotsky), socio‐cultural (Nardi and Engestrom) and community‐based (Wenger and Preece). Emerging from this review is the argument that effective e‐learning usually requires, or involves, high‐quality educational discourse, that leads to, at the least, improved knowledge, and at the best, conceptual development and improved understanding. To achieve this I argue that we need to adopt a more holistic approach to design that synthesizes features of the included approaches, leading to a framework that emphasizes the relationships between cognitive changes, dialogue processes and the communities, or contexts for e‐learning

Perceptions from Graduates of Professional Athletic Training Programs Involved in Peer-Assisted Learning

Context: Research has not explored how peer-assisted learning (PAL) impacts graduates once they are practicing as athletic trainers. Peer-assisted learning has been used in a variety of health education settings but there is a lack of data on its effects on the performance of graduates. Objective: To investigate professional graduates’ perceptions of PAL pedagogy in their athletic training education and the impact of that experience on their first job. Design: Qualitative study using a phenomenological approach. Setting: One-on-one phone interviews with athletic training graduates. Patients or Other Participants: Participants were from 8 accredited athletic training programs that varied in terms of the size of their institution, geographic location, number of graduates, and program directors’ willingness to promote the study. Thirteen (7 female, 6 male) 2010 (n ¼ 5) or 2011 (n ¼ 8) graduates volunteered for this study. Ten of the participants were from undergraduate baccalaureate athletic training programs, while 3 were from professional postbaccalaureate athletic training programs. Main Outcome Measure(s): One-on-one phone interviews were conducted with a structured interview protocol. Each participant was asked the same questions and allowed to clarify when needed. Interview data were analyzed inductively to uncover dominant themes, first by organizing the data, then by summarizing them into codes, and finally by interpreting them. Credibility was secured through a pilot study, member checking, triangulation, and peer debriefing. Results: Data were analyzed through a qualitative process; themes indicated graduates who have experienced PAL believe it led to improved communication and confidence, enhanced teaching skills, better clinical reasoning, improved socialization, and a deeper understanding that contributed to success on the Board of Certification examination. Conclusions: These findings are significant to the field of athletic training education as program directors investigate pedagogies that can assist students to think clinically as graduates. Evidence demonstrated that PAL does impact the students after graduation

Artificial Intelligence And Big Data Technologies To Close The Achievement Gap.

We observe achievement gaps even in rich western countries, such as the UK, which in principle have the resources as well as the social and technical infrastructure to provide a better deal for all learners. The reasons for such gaps are complex and include the social and material poverty of some learners with their resulting other deficits, as well as failure by government to allocate sufficient resources to remedy the situation. On the supply side of the equation, a single teacher or university lecturer, even helped by a classroom assistant or tutorial assistant, cannot give each learner the kind of one-to-one attention that would really help to boost both their motivation and their attainment in ways that might mitigate the achievement gap. In this chapter Benedict du Boulay, Alexandra Poulovassilis, Wayne Holmes, and Manolis Mavrikis argue that we now have the technologies to assist both educators and learners, most commonly in science, technology, engineering and mathematics subjects (STEM), at least some of the time. We present case studies from the fields of Artificial Intelligence in Education (AIED) and Big Data. We look at how they can be used to provide personalised support for students and demonstrate that they are not designed to replace the teacher. In addition, we also describe tools for teachers to increase their awareness and, ultimately, free up time for them to provide nuanced, individualised support even in large cohorts

The Presence and Possibility of Moral Sensibility in Beginning Pre-Service Teachers

This paper presents research on the moral sensibility of six pre-service teachers in an undergraduate teacher education program. Using their reflective writing across their first two semesters of coursework as well as focus group interviews in their third semester as sources of data, the paper identifies and describes three distinctive types of moral sensibility and examines ways in which moral sensibility interacts with experiences in teacher education. Suggestions for explicitly incorporating the moral in pre-service teacher education are presented

Towards a debugging tutor for object-oriented environments

Programming has provided a rich domain for Artificial Intelligence in Education and many systems have been developed to advise students about the bugs in their programs, either during program development or post-hoc. Surprisingly few systems have been developed specifically to teach debugging. Learning environment builders have assumed that either the student will be taught these elsewhere or thatthey will be learnt piecemeal without explicit advice.This paper reports on two experiments on Java debugging strategy by novice programmers and discusses their implications for the design of a debugging tutor for Java that pays particular attention to how students use the variety of program representations available. The experimental results are in agreement with research in the area that suggests that good debugging performance is associated with a balanced use ofthe available representations and a sophisticated use of the debugging step facility which enables programmers to detect and obtain information from critical momentsin the execution of the program. A balanced use of the available representations seemsto be fostered by providing representations with a higher degree of dynamic linkingas well as by explicit instruction about the representation formalism employed in the program visualisations

Editorial - Introduction to the special issue on deliberation with computers: exploring the distinctive contribution of new technologies to collaborative thinking and learning

Abstract not available