This study explores the impact of peer acknowledgement on learner engagement and implicit psychological attributes in written annotations on an online social reading platform. Participants included 91 undergraduates from a large North American University. Using log file data, we analyzed the relationship between learners’ received peer acknowledgement and their subsequent annotation behaviours using cross-lag regression. Higher peer acknowledgements correlate with increased initiation of annotations and responses to peer annotations. By applying text mining techniques and calculating Shapley values to analyze 1,969 social annotation entries, we identified prominent psychological themes within three dimensions (i.e., affect, cognition, and motivation) that foster peer acknowledgment in digital social annotation. These themes include positive affect, openness to learning and discussion, and expression of motivation. The findings assist educators in improving online learning communities and provide guidance to technology developers in designing effective prompts, drawing from both implicit psychological cues and explicit learning behaviours.

Psychological theories can inform the design of technology rich learning environments (TREs) to provide better learning and training opportunities. Research shows that learners do better when interacting with material that is situated in meaningful, authentic contexts. Recently, psychologists are interested in the role that emotion plays in learning with technology. Lajoie investigates the situations under which technology works best to facilitate learning and performance by examining the relations between cognition (problem solving, decision making), metacognition (self-regulation) and affect (emotion, beliefs, attitudes, interests, etc.) in medicine. Examples of advanced technologies to support medical students during critical thinking and problem solving, collaboration, and communication will be presented along with a description of multimodal methodologies for assessing the relationship between affect and learning in medical contexts. These methodologies include physiological and behavioral indices, think aloud protocols, eye tracking, self report, etc. Examples will be presented of how TREs can determine when learners are engaged and happy as opposed to bored and angry while learning. Findings from this type of research helps identify the best way to tailor the learning experience to the cognitive and affective needs of the learner.

The Deteriorating Patient Activity (DPA) is a real-life educational simulation that prepares medical students to effectively approach emergency situations through a role play where their instructor plays the role of a patient whose state is rapidly deteriorating. Although proven engaging and effective in improving student decision making, DPA is difficult to carry out since it requires students and medical instructors, all busy people, to be available at the same time and location. The present paper describes the "Digital" Deteriorating Patient Activity (DDPA), an agent-based tutoring system developed to allow learners to train on simple DPA cases so they can face more complex cases when meeting a human instructor.

Cultural profiling involves a complex interplay of multiple dimensions that are virtually impossible to wholly address. This paper explores several cultural (nationality and its associated Hofstede dimensions, religious beliefs), and demographic (gender, age) variables to evaluate if each of these are good candidates for predicting behavioural as well as cognitive attitudes related to computer use and learning activities. Results indicate that each variable taken individually will lead to limited success in attitudinal predictions. Several combinations of variables however could allow an interesting degree of prediction.

This paper reviews and integrates research that would be necessary to develop an AIED system able to detect and then appropriately react to an affective state of a learner. It addresses the nature of affect, methods to automatically detect affect, as well as the interplay between affect and learning-related cognition, and affective strategies that promote quality learning.

Our data on case creation demonstrated both validity and reliability issues concerning the generation of solutions to easy cases. We propose a methodology that addresses the challenge of capturing and representing evolving knowledge into a validation activity. . The primary emphasis of this activity is not on finding a reliable answer but on identifying and representing optimal reasoning processes leading to acceptable answers for each case. The study examines five medical experts' reasoning processes while they solve and teach three specific cases. Visual representations of their discourse and reasoning processes are co-constructed and consolidated. Findings indicate that variability can be explained by structuring cases around key processes.

EAGLE (Electronic Assistant for Game-Based Learning Experiences) is an intelligent tutoring system that supports learning with video games. We describe how a flexible ontology-based architecture can be used to model the learner, the game experience, and the domain of instruction. We then present an overview of how these elements interact within a learning experience.

Technology-rich environments provide the opportunity for medical students to develop expertise in clinical reasoning through deliberate practice with appropriate feedback. This study investigates whether feedback from intermediates may result in higher learning gains for novice medical students than feedback from experts.

It is clear that mood and emotion play an important role in how people deal with problems [1]. The problem-solving strategies adopted by people when they are in a happy mood are quite different than the strategies used by people when they are in a sad mood [1]. It is also well documented in the literature that individuals’ affective feelings influence their evaluative judgment, strategies of information processing, and the type of information retrieved from memory [1]. One area where this knowledge has important implications is in the design, application, and effectiveness of cognitive tools. Cognitive tools are tools that “help students during thinking, problem solving, or learning by providing them with opportunities to practice applying their knowledge in the context of complex, meaningful activities rather than in isolation of their ultimate use” (p. 88) [2]. A computer-based learning environment (CBLE) incorporating a number of cognitive tools of particular interest for this paper is called BioWorld [2]. BioWorld provides medical students with instruction, model proficiency, and an assessment of their knowledge in a more authentic scenario than standard classroom learning [2]. These tools have been shown to effectively promote scientific reasoning in high school students [3], and have been adapted for use with medical students. We propose replicating the emotional side of working in the medical field by manipulating the affect of students before they engage in a BioWorld problem. Addressing the relationship between mood and doctors’ performance is extremely important, especially with researchers suggesting that these types of emotions are normal, inevitable, and capable of negatively effecting patient care [4].