Elisabeth Paus

Learning through online peer discourse: Structural equation modeling points to the role of discourse activities in individual understanding

Although learning through discourse activities seems well-documented, it is unclear which mechanisms and behavioral variables are involved. What exactly contributes to learning when two or more learners interact in online learning environments? To analyze interrelations between central discourse activities and individual learning outcomes at the level of constructs, we applied structural equation modeling to data collected from 160 dyads engaging in written online learning discourses within a series of homogeneous experiments. We analyzed three theory-based indicators of conceptual elaboration activities during online discourse: the number of questions asked to receive information and expand knowledge, the number of explanations formulated to express individual knowledge, and the amount of on-task discourse. Individual conceptual understanding was represented by objective learning parameters that varied in each particular experimental task. These measured general understanding of the topic addressed and particular understanding of conceptual terms, complemented by the gain in individual self-assessed knowledge. Results of structural equation modeling revealed a strong effect of dyadic conceptual elaboration on individual understanding at the construct level, demonstrating that dyadic elaboration fosters the development of an elaborated individual understanding of specialist concepts and general content knowledge. Moreover, conceptual elaboration was best measured by the number of explanations during discourse. Implications regarding which features of collaborative learning settings promote mutual conceptual elaboration are discussed.

Patients medical knowledge and health counseling: What kind of information helps to make communication patient-centered?

OBJECTIVE To examine how physicians use information about a patients background knowledge when both anticipating what a patient knows and producing actual answers in an email counseling setting. METHODS A fictitious patient used a (high vs. low) level of technical jargon in an email inquiry about diabetes and provided explicit information on prior knowledge (high vs. low) through self-report. Final-year medical students (semi-experts) were asked to gauge the patients knowledge level (Experiment 1) and to produce an answer to the inquiry (Experiment 2). A total of N=150 participated in one of the two experiments. RESULTS Information from word usage and self-reports was used differently in the two experiments. A patient self-reporting low knowledge was assumed to have less background knowledge than one reporting some knowledge about the domain. The technicality of the patients word use influenced the answers: these were more technical when the inquiry used technical jargon instead of everyday language. CONCLUSION Knowledge anticipation and communication behavior in email health care seem to be guided by different hints regarding the patient, suggesting the existence of two separate mechanisms. PRACTICE IMPLICATIONS Beyond merely teaching physicians or health care providers to be aware of the patients knowledge level when formulating a patient-centered response, on-task methods should support health care providers during the actual communication phase by providing, for instance, metacognitive prompts.

Common Ground? How the Encoding of Specialist Vocabulary Affects Peer-to-Peer Online Discourse

Using the same specialist terms in online discourse can indicate knowledge overlaps between partners. However, linguistic overlaps do not automatically ensure overlaps in conceptual representations. In particular, learning situations, which typically focus on knowledge acquisition, require a sufficient understanding of domain-specific concepts. This study investigated how the same versus different lexical encodings of specialist concepts influenced peer-to-peer online discourse behavior and information exchange. Student dyads communicated via email while preparing a written text. Partners in each dyad received different texts containing either the same terminology across texts or different terminology. Results showed that dyads in the different-terminology condition communicated more intensively (e.g., clarifying the conceptual meaning of specialist terms by asking questions and giving explanations) than those in the same-terminology condition. However, despite exchanging more information, learners in the different-terminology condition were less certain about their conceptual understanding. Implications for the use of specialist language in peer-to-peer learning situations are discussed.

Toward an Integration of the Learning and Communication Perspectives in Computer-Supported Instructional Communication

Research on computer-supported instructional communication (CSIC) involves the study of interactions between instructors, learners, and system components in computer-based learning environments. At least two strands of research can be identified that are crucial for the understanding of CSIC: From the learning perspective, rooted in cognitive and educational psychology, CSIC is analyzed with regard to its potential for promoting specific cognitive processes, and thus ultimately for improving learning. From the communication perspective, rooted in social psychology and communication science, CSIC is analyzed with regard to conditions that affect its effectiveness and efficiency. CSIC researchers face the challenge of integrating the two traditionally separate research strands and their distinct methodological frameworks. In turn, new methods and findings emerging from an integrative application of research methods are leading to new conceptual challenges regarding the causal mechanisms mediating between the interindividual and the intraindividual levels in CSIC. We provide examples of CSIC research that demonstrate successful methodological integration, and introduce open conceptual challenges.