How teacher talk guidance during Invention activities shapes students’ cognitive engagement and transfer

Abstract

Background: A key question in K-12 STEM education is how best to guide students as they engage in exploratory learning activities so that students develop transferable knowledge. We investigated this question in a study of teacher talk guidance of an exploratory activity called Invention. In this study, teachers worked one-on-one with students, guiding them as they attempted to invent ratio-based equations of physical science phenomena. We applied the interactive, constructive, active, and passive (ICAP) framework as a theoretical lens through which to explore different forms of teacher talk guidance and resulting student talk. The ICAP hypothesis predicts that constructive engagement leads to greater learning than active engagement, which in turn leads to greater learning than passive engagement. However, students do not always enact the type of cognitive engagement that teachers prompt. In this paper, we work towards three goals: (1) to explore the forms of cognitive engagement prompted by teachers and enacted by students in their talk, (2) to test the ICAP hypothesis in the novel context of teacher-student dialog during Invention, and (3) to identify effective forms of teacher talk guidance for Invention activities and other exploratory STEM learning tasks. Results: While the majority of student talk was active, teachers produced an even distribution of constructive, active, and passive prompts. Teacher and student talk types tended to align, such that students often responded with the type of cognitive engagement teachers invited, with the exception of passive talk. In general, teacher talk showed the most robust relationship with students' abilities to transfer, while teacher-student dialog demonstrated a weaker relationship with transfer, and student talk was not significantly related to transfer. Some evidence for the ICAP hypothesis was found, most prominently in teacher talk, where constructive prompts positively predicted transfer, active prompts were not related to transfer, and passive prompts negatively predicted transfer. Conclusions:This research implies that teachers should use a large proportion of constructive prompts and relatively few passive ones when guiding students through Invention tasks, when the goal is to provoke transfer of learning to novel contexts. This work also extends the CAP portion of the ICAP hypothesis to teacher-student dialog and underscores the teacher's critical role in encouraging students to cognitively engage with exploratory STEM tasks in effective ways.

Exploring the Relationship between Teacher Knowledge and Active-Learning Implementation in Large College Biology Courses

“…Others provided vague questions that likely left students unsure of what they were supposed to do, such as “Talk to your neighbor about this figure.” Though students in these courses worked during class, class time may not have been well spent, because the questions did not challenge students to generate their own understandings. Our approach, and other research, indicates that the ICAP framework can be useful for making finer distinctions in instructional practice (Chi and Wylie, 2014; Wiggins et al , 2017; Chase et al ., 2019). Finer distinctions in practices, such as contrasting active versus generative active-learning instruction, will be critical to investigating in more detail how teaching practices influence student success.…”

“…Knight and colleagues (2013) found that undergraduates who were explicitly prompted by instructors to use reasoning were more likely to have discussions containing evidence-based reasoning than students not prompted in this way. A study of middle school teachers and students similarly indicated that students were more likely to generate their own explanations and reasoning when the teacher gave a question or prompt that asked students to explain or generate new ideas or reasoning (i.e., generative prompt), compared with when the instructor asked questions probing for recall (i.e., active prompt; Chase et al , 2019). Additionally, greater use of generative prompts by teachers were associated with better student performance on questions testing their ability to transfer knowledge to novel problems (Chase et al ., 2019).…”

“…A study of middle school teachers and students similarly indicated that students were more likely to generate their own explanations and reasoning when the teacher gave a question or prompt that asked students to explain or generate new ideas or reasoning (i.e., generative prompt), compared with when the instructor asked questions probing for recall (i.e., active prompt; Chase et al , 2019). Additionally, greater use of generative prompts by teachers were associated with better student performance on questions testing their ability to transfer knowledge to novel problems (Chase et al ., 2019). Future work must investigate whether helping undergraduate biology instructors develop knowledge of how people learn and how to apply that knowledge while teaching improves their students’ learning.…”

Trainee Perceptions of Instructional Design in Continuous Online Training and Learning Transfer

“…Transfer in online training is also favoured through dialogue between trainers and trainees and collaboration between trainees [14,21]. In distance learning, the tutor has the role of advising, guiding, and motivating participation, interest, and reflection through the dialogue carried out throughout learning and in follow-up activities [18].…”

Individual preparation for collaborative learning: Systematic review and synthesis

“…However, research findings reveal considerable variability concerning the superiority or inferiority of collaborative as compared to individual learning in view of inferencing indicators (Andrews & Rapp, 2015;Menekse & Chi, 2019;Nokes-Malach et al, 2015). Moreover, in studies which explicitly investigate learners' collaboration activities, it is frequently observed that collaborating learners often tend to restate what has already been given instead of drawing inferences (Chase et al, 2019;Chi & Menekse, 2015;Roscoe & Chi, 2007;Webb, 2013). To explain these findings, cognitive costs are proposed in terms of collaborative learning putting higher demands on the learners' cognitive resources than individual learning.…”