Visualising the temporal aspects of collaborative inquiry-based learning processes in technology-enhanced physics learning

Abstract

This study presents new ways of visualising technology-enhanced collaborative inquiry-based learning (CIBL) processes in an undergraduate physics course. The data included screen-capture videos from a technology-enhanced learning environment and audio recordings of discussions between students. We performed a thematic analysis based on the phases of inquiry-based learning (IBL). The thematic analysis was complemented by a content analysis, in which we analysed whether the utilisation of technological tools was on a deep-level, surface-level, or nonexistent basis. Student participation was measured in terms of frequency of contributions as well as in terms of impact. We visualised the sequence of the face-to-face interactions of two groups of five students by focussing on the temporal aspects of IBL, technology enhancement and collaborative learning. First, instead of the amount of time the groups spent on a specific IBL phase, the between-group differences in the most frequent transitions between the IBL phases determined their differential progress in the CIBL process. Second, we found that the transitions were triggered by the groups' ways of utilising technological tools either at the deep level or at the surface level. Finally, we found that the level of participation inequity remained stable throughout the CIBL process. As a result, only some of the members of the groups played a role in the most frequent transitions. Furthermore, this study reveals the need for scaffolds focussing on inquiry, technological and collaborative skills at the beginning of the learning process.

When coding-and-counting is not enough: using epistemic network analysis (ENA) to analyze verbal data in CSCL research

“…However, this violates a persistent finding in educational research: there are often differences between two instances of the same action (Lämsä et al 2018;Roschelle and Teasley 1995;Shaffer 2006). For example, in the discussion presented in Table 2, two learners discuss possible reasons (Code "HG") for the problem of an underperforming student.…”

The effectiveness of video-based interaction on professional science teachers to improve elementary school students achievements

“…The characteristic of the inquiry model is that it raises the phenomenon. Engagement to phenomena can be explored through videos, images, and experiment kits in urban environments (Lämsä, Hämäläinen, Koskinen & Viiri, 2018). An urban environment may be considered to have better learning resource facilities than a rural setting.…”

Deep Networks for Collaboration Analytics: Promoting Automatic Analysis of Face-to-Face Interaction in the Context of Inquiry-Based Learning

“…While various tools to guide the different phases of CSCIL have been developed (see Bell et al, 2010;Zacharia et al, 2015), which in addition consider contextual factors (such as the nature of inquiry problems or the age of learners), implementing timely guidance requires that the phase of the learners' CSCIL processes be known. There are technological learning environments that allow the implementation of pre-structured CSCIL assignments based on the different IBL phases (e.g., Go-Lab;van Joolingen et al, 2005), but CSCIL taking place in face-to-face interaction may be less predictable (see Lämsä et al, 2018;2020) and more fragmented than the computer-mediated interaction (Sins et al, 2011). Thus, there is a need to examine whether collaboration analytics can be applied to study these dynamic and sometimes fragmented face-toface conversations.…”

“…The aim of the assignment was to study how the displacement of an atom in two-dimensional gas depends on time by using a Python program (Figure 1). In our previous studies (Lämsä et al, 2018;2020), we identified tasks that learners should do in the different IBL phases. In the orientation phase, learners should identify the main concepts of the assignment and become familiar with the Python program.…”

“…Finally, in the discussion phase, learners should elaborate the findings and conclusions as well as reflect on the joint CSCIL process. CSCIL processes are rarely linear, but learners move back and forth between the different phases (see Section 1.2 and Lämsä et al, 2018;2020). We captured the CSCIL processes of 11 groups solving the random walk problem by screen-capturing videos of the computer screen and audio recordings.…”