Susanne P. Lajoie

Transitions and Trajectories for Studies of Expertise

The transition from student to expert professional can be accelerated when a trajectory for change is plotted and made visible to learners. Trajectories or paths toward expertise are domain specific and must first be documented and then used within instructional contexts to promote knowledge transitions. This article describes how models of expertise can serve to help students attain higher levels of competence.

Three Myths? The Over-Representation of the Gifted among Dropouts, Delinquents, and Suicides.

one (Barnes, 1973). Hecht (1975) asked why the academically gifted and potential dropouts are traditionally viewed at opposite ends of a continuum. Using teacher ratings, he found 20% of potential dropouts came from families on welfare, while only 3% of this group were described as academically gifted. Academically gifted subjects were described as coming from stable homes of the majority culture, obtaining good grades, and being well adjusted. Opposite characteristics were described for potential dropouts. Hecht pointed that teachers may be confusing academic gifted-

Individual Differences in Spatial Ability: Developing Technologies to Increase Strategy Awareness and Skills

Individual differences in spatial ability were explored among educational psychology and engineering students as they related to performance on a real-world spatial task known as the orthographic projection task. As expected, educators performed higher on verbal aptitude tests than engineers, and engineers performed higher on spatial aptitude tests than psychologists. A detailed cognitive task analysis revealed specific spatial strategies for solving the orthographic projection tasks. These detailed strategies were used to design a computerized learning environment called the orthographic projection tutor (OPT). Pre- and posttests of orthographic projections were administered to a treatment group and 2 control groups. The results indicated that spatial processes could be identified and taught to certain individuals. Aptitude process research can lead to prescriptive forms of adaptive technology. The connection between theory and the design of computer-based learning environments is discussed.

Scaffolding problem-based learning with CSCL tools

Small-group medical problem-based learning (PBL) was a pioneering form of collaborative learning at the university level. It has traditionally been delivered in face-to-face text-based format. With the advancement of computer technology and progress in CSCL, educational researchers are now exploring how to design digitally-implemented scaffolding tools to facilitate medical PBL. The “deteriorating patient” (DP) role play was created as a medical simulation that extends traditional PBL and can be implemented digitally. We present a case study of classroom usage of the DP role play that examines teacher scaffolding of PBL under two conditions: using a traditional whiteboard (TW) and using an interactive whiteboard (IW). The introduction of the IW technology changed the way that the teacher scaffolded the learning. The IW showed the teacher all the information shared within the various subgroups of a class, broadening the basis for informed classroom scaffolding. The visual records of IW usage demonstrated what students understood and reduced the need to structure the task. This allowed more time for engaging students in challenging situations by increasing the complexity of the problem. Although appropriate scaffolding is still based on the teacher’s domain knowledge and pedagogy experience, technology can help by expanding the scaffolding choices that an instructor can make in a medical training context.

AI in medical education—another grand challenge for medical informatics

The potential benefits of artificial intelligence in medicine (AIM) were never realized as anticipated. This paper addresses ways in which such potential can be achieved. Recent discussions of this topic have proposed a stronger integration between AIM applications and health information systems, and emphasize computer guidelines to support the new health care paradigms of evidence-based medicine and cost-effectiveness. These proposals, however, promote the initial definition of AIM applications as being AI systems that can perform or aid in diagnoses. We challenge this traditional philosophy of AIM and propose a new approach aiming at empowering health care workers to become independent self-sufficient problem solvers and decision makers. Our philosophy is based on findings from a review of empirical research that examines the relationship between the health care personnels level of knowledge and skills, their job satisfaction, and the quality of the health care they provide. This review supports addressing the quality of health care by empowering health care workers to reach their full potential. As an aid in this empowerment process we argue for reviving a long forgotten AIM research area, namely, AI based applications for medical education and training. There is a growing body of research in artificial intelligence in education that demonstrates that the use of artificial intelligence can enhance learning in numerous domains. By examining the strengths of these educational applications and the results from previous AIM research we derive a framework for empowering medical personnel and consequently raising the quality of health care through the use of advanced AI based technology.

Technology-Rich Tools to Support Self-Regulated Learning and Performance in Medicine

Medical students’ metacognitive and self-regulatory behaviors are examined as they diagnose patient cases using BioWorld, a technology rich learning environment. BioWorld offers an authentic problem-based environment where students solve clinical cases and receive expert feedback. We evaluate the effectiveness of key features in BioWorld (the evidence table and visualization maps) to see whether they promote metacognitive monitoring and evaluation. Learning outcomes were assessed through novice/expert comparisons in relation to diagnostic accuracy, confidence, and case summaries. More specifically we examined how diagnostic processes and learning outcomes were refined or improved through practice at solving a series of patient cases. The results suggest that, with practice, medical students became more expert-like in the processes involved in making crucial clinical decisions. The implications of these findings for the design of features embedded within BioWorld that foster key metacognitive and self-regulatory processes are discussed.

The Creation of Virtual and Face-to-Face Learning Communities: An International Collaboration Experience

This article examines the use of technology in higher education to support an international collaboration between 2 graduate seminars in cognition and instruction, one in Mexico and another in Canada. The culture of both seminars is described in the context of using computer mediated collaboration systems. The online collaboration between and within the 2 groups happened through the use of the communications tools available in WebCT, a Web-based course management system. The analyses reveal the discursive patterns between instructors and students in both settings, with an examination of teacher presence as it pertains to a cognitive apprenticeship perspective, with particular attention to teachers modeling and scaffolding. We also present the nature of the student interactions in terms of the cognitive elements present in the discourse and the types of social interactions that support the community of inquiry model. Students in both seminars revealed high levels of critical thinking in the types of discussions they engaged in and the types of questions they posed to others. Differences were noted in the types of teacher modeling in the 2 seminars. These differences are explored and future directions are stated for promoting international collaborations in higher education.

Cognitive Tools for Assessment and Learning in a High Information Flow Environment.

A simulation-based intelligent tutoring system (ITS) was designed for nurses working in a Surgical Intensive Care Unit (SICU). A cognitive task analysis approach was used to identify the cognitive components of clinical decision making of “expert” surgical nurses. Quantitative analyses revealed that expert nurses reached the same decisions. However, a qualitative analysis of the verbal protocols revealed great variability in how the nurses arrived at their clinical decisions. Differences were observed in: hypothesis generation, planning of medical interventions, actions performed, results of evidence gathering, interpretation of the results, heuristics, and the overall solution paths. The results of these analyses were used to design a prototype ITS. The tutoring environment (SICUN) is described in terms of the cognitive tools it provides, and the assessment opportunities it presents. Implications for the evaluation of this system are discussed.

Empowering children in the use of statistics

Abstract Statistics pervade our society, yet the understanding of statistics has remained the domain of a select few. Although the majority of the literature has focused on the adult learner, there is a movement toward teaching statistics to children. This article addresses the ways in which the study of statistics has been examined in the elementary and secondary schools in terms of content, readiness of children to learn, pedagogy, and assessment. A proposal is presented of how a cognitive apprenticeship model can be developed from the empirical research findings in order to build more effective instructional and assessment methods for statistics education.

The role of regulation in medical student learning in small groups

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.