Modeling individual and collaborative problem-solving in medical problem-based learning

Today a great many medical schools have turned to a problem-based learning (PBL) approach to teaching as an alternative to traditional didactic medical education to teach clinical-reasoning skills at the early stages of medical education. While PBL has many strengths, effective PBL tutoring is time-intensive and requires the tutor to provide a high degree of personal attention to the students, which is difficult in the current academic environment of increasing demands on faculty time. This paper describes the student modeling approach used in the COMET intelligent tutoring system for collaborative medical PBL. To generate appropriate tutorial actions, COMET uses a model of each student’s clinical reasoning for the problem domain. In addition, since problem solving in group PBL is a collaborative process, COMET uses a group model that enables it to do things like focus the group discussion, promote collaboration, and suggest peer helpers. Bayesian networks are used to model individual student knowledge and activity, as well as that of the group. The validity of the modeling approach has been tested with student models in the areas of head injury, stroke, and heart attack. Receiver operating characteristic (ROC) curve analysis shows that the models are highly accurate in predicting individual student actions. Comparison with human tutors shows that the focus of group activity determined by the model agrees with that suggested by the majority of the human tutors with a high degree of statistical agreement (McNemar test, p = 0.774, Kappa = 0.823).     

Designing automated adaptive support to improve student helping behaviors in a peer tutoring activity

Adaptive collaborative learning support systems analyze student collaboration as it occurs and provide targeted assistance to the collaborators. Too little is known about how to design adaptive support to have a positive effect on interaction and learning. We investigated this problem in a reciprocal peer tutoring scenario, where two students take turns tutoring each other, so that both may benefit from giving help. We used a social design process to generate three principles for adaptive collaboration assistance. Following these principles, we designed adaptive assistance for improving peer tutor help-giving, and deployed it in a classroom, comparing it to traditional fixed support. We found that the assistance improved the conceptual content of help and the use of interface features. We qualitatively examined how each design principle contributed to the effect, finding that peer tutors responded best to assistance that made them feel accountable for help they gave.     

Supporting collaborative learning and problem-solving in a constraint-based CSCL environment for UML class diagrams

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 collaboration. Being one of constraint-based tutors, COLLECT-UML represents the domain knowledge as a set of constraints. However, it is the first system to also represent a higher-level skill such as collaboration using the same formalism. We started by developing a single-user ITS that supported students in learning UML class diagrams. The system was evaluated in a real classroom, and the results showed that students’ performance increased significantly. In this paper, we present our experiences in extending the system to provide support for collaboration as well as domain-level support. We describe the architecture, interface and support for collaboration in the new, multi-user system. The effectiveness of the system has been evaluated in two studies. In addition to improved problem-solving skills, the participants both acquired declarative knowledge about effective collaboration and did collaborate more effectively. The participants have enjoyed working with the system and found it a valuable asset to their learning.     

Developing sound tutor training for online writing centers: creating productive peer reviewers

It is our experience that tutors trained for face-to-face writing centers are not adequately prepared for the challenges they encounter working with online writing centers. The purpose of our article is to provide an overview—especially for administrators, developers, and tutors new to electronic tutoring environments—of the issues and considerations unique to online tutoring that training programs need to address. In our discussion, we hope to engender enthusiasm for online tutoring by discussing three aspects of online tutoring: appreciating text-only environments, developing procedures for responding online, and creating appropriate roles for online tutors. We offer suggestions about how to address these three aspects in online tutor training, and we suggest that addressing these issues leads to an understanding of the online tutor as a productive peer reviewer.     

Diagnosing and acting on student affect: the tutor’s perspective

In this paper we explore human tutors’ inferences in relation to learners’ affective states and the relationship between those inferences and the actions that tutors take as their consequence. At the core of the investigations presented in this paper lie fundamental questions associated with the role of affective considerations in computer-mediated educational interactions. Theory of linguistic politeness is used as the basis for determining the contextual factors relevant to human tutors’s actions, with special attention being dedicated to learner affective states. A study was designed to determine what affective states of the learners are relevant to tutoring mathematics and to identify the mechanisms used by tutors to predict such states. Logs of tutor-student dialogues were recorded along with contextual factors taken into consideration by tutors in relation to their specific tutorial dialogue moves. The logs were annotated in order to determine the types and range of student and tutor actions. Machine learning techniques were then applied to those actions to predict the values of three factors: student confidence, interest and effort. Whilst due to limited size and sparsity of data the results are not conclusive, they are very valuable as the basis for empirically derived hypotheses to be tested in further studies. The potential implications of the hypotheses, if they were confirmed by further studies, are discussed in relation to the impact of tutor’s ability to diagnose student affect on the nature of computer-mediated tutorial interactions.     

Collaborative learning with a wiki: Differences in perceived usefulness in two contexts of use

This paper investigates the potential of a wiki (FlexWiki) to support collaborative authoring of web resources in authentic coursework by two different sets of education students at different stages of their professional development. Research questions included: (1) how the selected wiki could be blended with curriculum activities and existing technologies to complete collaborative tasks; (2) student and tutor expectations concerning collaborative learning and whether these expectations were met; (3) the barriers and enablers of using the wiki and perceptions of the task‐technology fit. Key findings included that tutors and students were able to use the wiki to complete tasks; tutors and students were positive about learning outcomes but collaboration was not as co‐constructive as hoped for; there were tensions between expectations of collaboration and assessment practices that affected how students collaborated; differences between participants in their group interaction, degree of co‐presence and familiarity with technology led to differences in perceptions of usefulness and actual wiki use; and version‐tracking data from the wiki proved unreliable on its own for gaining insights into actual collaborative processes. These findings suggest the importance of considering detailed local contexts of use when deciding to adopt new tools for supporting collaboration.     

Measuring causality between collaborative and individual gaze metrics for collaborative problem-solving with intelligent tutoring systems

When students are working collaboratively and communicating verbally in a technology-enhanced environment, the system cannot track what collaboration is happening outside of the technology, making it difficult to fully assess the collaboration of the students and adapt accordingly. In this article, we propose using gaze measures as a proxy for cognitive processes to achieve collaboration awareness. Specifically, we use Granger causality to analyse the causal relationships between collaborative and individual gaze measures from students working on a fractions intelligent tutoring system and the influence that the students' dialogue, prior knowledge, or success has on these relationships. We found that collaborative gaze patterns drive the individual focus in the pairs with high posttest scores and when they are engaged in problem-solving dialogues but the opposite with low performing students. Our work adds to the literature by extending the correlational relationships between individual and collaborative gaze measures to causal relationships and suggests indicators that can be used within an adaptive system.     

Toward an Affect-Sensitive AutoTutor

Here, we consider the possibility of enabling AutoTutor, an intelligent tutoring system, to process learners' affective and cognitive states. AutoTutor is a fully automated computer tutor that simulates human tutors and converses with students in natural language.     

Reciprocal tutoring using cognitive tools

Abstract Reciprocal tutoring, where peers take turns to tutor each other, is an interesting style of social learning. In the Reciprocal Tutoring System (RTS), three computational cognitive tools were designed to facilitate reciprocal tutoring of Lisp programming on the network. The first is a Petal-style of code–chunk interface, with which a tutee can enter Lisp code without making syntactic errors. The second tool is Diagnosis-Hint Tree, with which a tutor can diagnose and comment on the errors in the tutee's program. The third one is a list of dialogue templates, with which the tutee and the tutor can communicate during the tutoring process. A three-phase experiment was conducted, with each phase using different cognitive tools. In addition, with the help of the cognitive tools, RTS provides a virtual learning companion that can play tutor or tutee. Evaluation results reveal both the strengths and weaknesses of peer-based learning and intelligent tutoring, with supports of different cognitive tools. Peer-based learning supported by cognitive tools is a practical and attractive alternative to intelligent tutoring systems. Exactly which type of tutor is preferred depends on the tutee's cognitive, communication, and emotional needs in the tutorial context.     

Collaborative Problem Solving and Groupware for Software Development

When a group is working together toward a common goal, communication and collaboration are key. This is especially true in software development where a project of any significance involves groups of people. Collaborative problem-solving techniques and groupware technology can be a boon to software development because they enhance communication and cooperation. This article examines how software development is affected by collaborative problem solving and decision making, groupware theory and tools, and group cognition and psychology. It also analyzes collaboration tools and their correlation to problem solving and group characteristics.     

An approach to developing computational supports for reciprocal tutoring

This study presents a novel approach to developing computational supports for reciprocal tutoring. Reciprocal tutoring is a collaborative learning activity, where two participants take turns to play the role of a tutor and a tutee. The computational supports include scaffolding tools for the tutor, and a computer-simulated virtual participant. The approach, including system architecture, implementations of scaffolding tools for the tutor and of a virtual participant is presented herein. Furthermore, a system for reciprocal tutoring is implemented as an example of the approach.     

COMET: A Collaborative Tutoring System for Medical Problem-Based Learning

This paper discussed about the developed collaborative intelligent tutoring system for medical PBL called Comet (collaborative medical tutor). Comet uses Bayesian networks to model the knowledge and activity of individual students as well as small groups. It applies generic tutoring algorithms to these models and generates tutorial hints that guide problem solving. An early laboratory study shows a high degree of agreement between the hints generated by Comet and those of experienced human tutors. Evaluations of Comet's clinical-reasoning model and the group reasoning path provide encouraging support for the general framework.     

A case study-based investigation of students’ experiences with social software tools

The term “social software” covers a range of tools which allow users to interact and share data with other users, primarily via the web. Blogs, wikis, podcasts and social networking websites are some of the tools that are being used in educational, social and business contexts. We have examined the use of social software in the UK further and higher education to collect evidence of the effective use of social software in student learning and engagement. We applied case study methodology involving educators and students from 26 initiatives. In this paper, we focus on the student experience: educational goals of using social software; benefits to the students; and the challenges they experience. Our investigations have shown that social software supports a variety of ways of learning: sharing of resources; collaborative learning; problem-based and inquiry-based learning; and reflective learning. Students gain transferable skills of team working, negotiation, communication and managing digital identities. Although these tools enhance a student's sense of community, the need to share and collaborate brings in additional responsibility and workload, which some students find inflexible and “forced”. Our findings show that students have concerns about usability, privacy and the public nature of social software tools for academic activities.     

Role of relativistic knowledge in intelligent tutoring

Understanding complex cognitive behavior necessarily involves interaction between two (or more) individuals. The teaching-learning process is just a special case. From the standpoint of an intelligent tutor (or human teacher) all student/learner knowledge is either assumed to be available or is judged relative to the teacher's model(s) of the content and/or skills to be acquired. In this regard, learner models play a central role in most contemporary approaches to intelligent tutoring. These models typically assign to the learner certain capabilities which are assumed by the intelligent tutor in administering instruction. If too much is assumed, however, it is impossible to determine where the student is going wrong, or how to correct the problem—unless the tutor model is enhanced to incorporate the assumed capabilities and these capabilities correspondingly are eliminated from the learner model. Research associated with the Structural Learning Theory shows that a common “goal switching” control mechanism is all that may safely be assumed with confidence. Maximum flexibility is achieved by assuming only this mechanism, along with basic encoding and decoding capabilities.     

Tutoring executives online: what drives perceived quality?

Studies of learning and student satisfaction in the context of online university programmes have largely neglected programmes catering specifically to business executives. Such executives have typically been away from higher education for a number of years, and have collected substantial practical experience in the subject matters they are taught. Their expectations in terms of both content and delivery may therefore be different from non-executive students. We explore perceptions of the quality of tutoring in the context of an online executive MBA programme through participant interviews. We find that in addition to some of the tutor behaviours already discussed in the literature, executive students look specifically for practical industry knowledge and experience in tutors, when judging how effective a tutor is. This has implications for both the recruitment and training of online executive MBA tutors.     

Collaborative learning in an educational robotics environment

Learning to collaborate is an important educational goal. The concept of collaborative learning is differently defined by several authors. Problem solving and problem-based learning are also important in our educational framework. We shall situate and clarify here the instructional design concepts used in an educational setting based on a “collaborative and problem based learning environment” applied to educational robotics. Educational robotics activities are developed at several school levels (primary, secondary) and in adults' training contexts. The instructional design of such learning activities is based on a constructivist approach of learning. Their educational objectives are varied. In our approach, the goal is not only that the learners acquire specific skills (e.g. knowledge on electricity, electronics, robotics…), but also and mainly demultiplicative, strategic and dynamic skills. The methodology focuses on collaboration to design and develop common projects and on problem solving skills development. The pupils work in small groups (2–4). In the reported research, some learners' interactions have been observed during the activity in a primary school with an observation grid. The analysis of the verbalisations between the learners and their actions on the computers, and the robotics materials coming from those observations offer the opportunity to study the way the learners are collaborating.     

Weathering wikis: Net-based learning meets political science in a South African university

Wikis represent flexible tools functioning as open-ended environments for collaboration while also offering process and group writing support. Here we focus on a project to innovate the use of wikis for collaborative writing within student groups in a final-year undergraduate political science course. The primary questions guiding our research were in what ways could wikis assist collaborative learning in an undergraduate course in political science and how we could support educators’ in the effective use of wikis? Curiously, wikis may serve as a mediating artifact for collaborative writing even among students who are reluctant to post online drafts. The paper raises questions concerning the nature and limits of lecturer and tutor power to deliver transformative educational innovations in relation to the capacity of students to embrace, comply with, or resist such innovation. In analysing the negotiation of the use of wikis in the course by and among the lecturer, tutors, and students, we draw on two principles in activity theory, which Yrjö Engeström argued are central to his model of expansive learning: multi-voicedness and contradictions [Engeström, Yrjö. (1987). Learning by expanding: An activity-theoretical approach to developmental research. Helsinki: Orienta-Konsultit; Engeström, Yrjö. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of Education and Work14(1), 133-156.]. We add a third principle, transparency, to more fully capture what we observed.