Using Online Digital Tools and Video to Support International Problem-Based Learning

The goal of this study is to examine how to facilitate cross-cultural groups in problem-based learning (PBL) using online digital tools and videos. The PBL consisted of two video-based cases used to trigger student-learning issues about giving bad news to HIV-positive patients. Mixed groups of medical students from Canada and Hong Kong worked with facilitators from each country along with an expert facilitator. The study used AdobeConnect to support the international model through synchronous video interaction and shared applications. This study examines strategies and challenges in facilitating PBL across distance and cultures. Discourse was analyzed using both an inductive and deductive approach where the later used the Community of Inquiry coding scheme. The international context provides a way to facilitate multiple perspectives about how to communicate bad news to patients from different cultural backgrounds. In addition, we present the results of an exploratory analysis of pre and post tests using a standardized patient that demonstrate that the students’ pattern of communication showed qualitative change. Several conjectures were developed for future research

Developing an agent-based adaptive system for scaffolding self-regulated inquiry learning in history education

This article presents a methodology for modelling the development of self-regulated learning skills in the context of computer-based learning environments using a combination of tracing techniques. The user-modelling techniques combine statistical and computational approaches to assess skill acquisition, practice, and refinement with the MetaHistoReasoning tool, a single-agent system that supports inquiry-based learning in the domain of history. Data were collected from twenty-two undergraduate students during a 4-h session where user interactions were logged by the system. A logistic regression model predicted user performance in relation to a skill categorization task with 75 % accuracy. The manner in which users apply the skills that are acquired is then assessed through a rule-based reasoning system that allows the pedagogical agent to adapt instruction. The results show that the model allows the agent to detect instances when skills are inappropriately applied as well as what type of goal that is pursued by students. We discuss the implications of these user-modelling techniques in terms of sequencing instructional content and using the tutoring agent to deliver several types of discourse moves in order to enhance learning

A domain-specific account of self-regulated learning: the cognitive and metacognitive activities involved in learning through historical inquiry

Educational researchers have recently begun to conceptualize theoretical constructs and mechanisms of metacognitive activities in terms of the features that are specific to particular academic domains and subject matter. In this paper, we propose a framework of domain-specific metacognition in relation to learning through historical inquiry. The framework postulates that students’ comprehension of historical events is mediated by a state of coherence in understanding the causes that explain why an event occurred. Comprehension breaks down when the causes that explain the occurrence of historical events are unknown, uncertain, or unreported. In order to reinstate coherence in understanding, students engage in cognitive and metacognitive activities in accordance with disciplinary-based practices. Drawing on the existing empirical evidence, we discuss how the study of self-regulatory processes contributes to our understanding of the challenges faced by students while learning about complex historical topics as well as the skills that are required to gain knowledge while investigating the past

Advancing teacher technology education using open-ended learning environments as research and training platforms

A primary concern of teacher technology education is for pre-service teachers to develop a sophisticated mental model of the affordances of technology that facilitates both teaching and learning with technology. One of the main obstacles to developing the requisite technological pedagogical content knowledge is the inherent challenge faced by teachers in monitoring and controlling certain aspects of their own learning while navigating the web and designing a lesson plan. This paper reviews preliminary findings obtained in our research with nBrowser, an intelligent web browser designed to support pre-service teachers’ self-regulated learning and acquisition of technological pedagogical content knowledge. Case examples of data mining techniques are presented that allow the discovery of knowledge regarding pre-service teachers’ information-seeking and acquisition behaviours and how to support them. The first case illustrates the use of simulated learner experiments, while the second involves the creation of a model to detect learner behaviours. We discuss the implications in terms of design guidelines recommendations for nBrowser as well as the broader impacts for future research on technological pedagogical content knowledge research and development

Mining learner-system interaction data: Implications for modeling learner behaviors and improving overlay models

A growing body of empirical evidence suggests that the adaptive capabilities of computer-based learning environments can be improved through the use of educational data mining techniques. Log-file trace data provides a wealth of information about learner behaviors that can be captured, monitored, and mined for the purposes of discovering new knowledge and detecting patterns of interest. This study aims to leverage these analytical techniques to mine learner behaviors in relation to both diagnostic reasoning processes and outcomes in BioWorld, a computer-based learning environment that support learners to practice solving medical problems and receive formative feedback. In doing so, hidden Markov models are used to model behavioral indicators of proficiency during problem solving, while an ensemble of text classification algorithms are applied to written case summaries that learners’ write as an outcome of solving a case in BioWorld. The application of these algorithms characterize learner behaviors at different phases of problem solving which provides corroborating evidence in support of where revisions can be made to provide design guidelines of the system. We conclude by discussing the instructional design and pedagogical implications for the novice–expert overlay system in BioWorld, and how the findings inform the delivery of feedback to learners by highlighting similarities and differences between the novice and expert trajectory toward solving problems

A Tale of Three Cases: Examining Accuracy, Efficiency, and Process Differences in Diagnosing Virtual Patient Cases

Clinical reasoning is a central skill in diagnosing cases. However, diagnosing a clinical case poses several challenges that are inherent to solving multifaceted ill-structured problems. In particular, when solving such problems, the complexity stems from the existence of multiple paths to arriving at the correct solution (Anonymous, 2003). Moreover, the approach one employs in diagnosing a clinical case is in some measure dependent upon the complexity of the case. This leads us to the question: Are there differences in the manner in which novices solve cases with varying levels of complexity in a computer based learning environment? More specifically, we are interested in understanding and elucidating if there are clinical reasoning differences in regards to accuracy, efficiency, and process across three virtual patient cases of varying difficulty levels. Examining such differences may have implications from both a learner modeling and system enhancement perspective. We close by discussing the implications for practice, limitations of the study, and future research directions

Using online digital tools and video to support international problem-based learning

The goal of this study is to examine how to facilitate cross-cultural groups in problem-based learning (PBL) using online digital tools and videos. The PBL consisted of two video-based cases used to trigger student-learning issues about giving bad news to HIV-positive patients. Mixed groups of medical students from Canada and Hong Kong worked with facilitators from each country along with an expert facilitator. The study used AdobeConnect to support the international model through synchronous video interaction and shared applications. This study examines strategies and challenges in facilitating PBL across distance and cultures. Discourse was analyzed using both an inductive and deductive approach where the later used the Community of Inquiry coding scheme. The international context provides a way to facilitate multiple perspectives about how to communicate bad news to patients from different cultural backgrounds. In addition, we present the results of an exploratory analysis of pre and post tests using a standardized patient that demonstrate that the students’ pattern of communication showed qualitative change. Several conjectures were developed for future research

The role of regulation in medical student learning in small groups: Regulating oneself and others’ learning and emotions

Computer supported collaborative problem based learning in medicine can lead to high levels of metacognition.High co-regulation in problem based learning co-occurs with levels of Interactive Social Presence.Co-regulatory actions that activate the discussion and metacognitive acts of planning. This study examines the role of regulatory processes in medical students as they learn to deliver bad news to patients in the context of an international web-based problem based learning environment (PBL). In the PBL a medical facilitator and students work together to examine video cases on giving bad news and share their perspectives on what was done effectively and what could be done differently. We examine how regulation occurs within this collaboration. A synchronous computer-supported collaborative learning environment (CSCL) facilitated peer discussion at a distance using a combination of tools that included video-conferencing, chat boxes, and a shared whiteboard to support collaborative engagement. We examine regulation along a continuum, spanning from self- to co-regulation, in situations where medical students learn how to manage their own emotions and adapt their responses to patient reactions. We examine the nature of the discourse between medical students and facilitators to illustrate the conditions in which metacognitive, co-regulation and social emotional activities occur to enhance learning about how to communicate bad news to patients