March 25, 2018
March 25, 2018
March 27, 2018
While active learning is acknowledged to “work” through numerous pair-wise studies comparing it against traditional lecture, it is important that we continue to unpack the nuances of active learning (Streveler & Menekse, 2017). This is necessary in order to “design instruction that matches kinds of activities to the importance and difficulty of outcomes to be achieved” (Streveler & Menekse, 2017, p. 189) and so that we are better equipped to support faculty in appropriately implementing active learning.
Streveler and Menekse (2017) propose two frameworks to unpack and classify active learning activities: ICAP (Chi, 2009) and KIE (Linn, 1995). When studied and more thoughtfully understood, these two frameworks provide interesting perspectives on active learning from a research perspective. However, we have noted that these frameworks can lead to further confusion when working with faculty who are trying to implement and evaluate active learning (Authors, 2017). In this paper, we propose, an alternate framework for helping faculty engage with active learning: Engineering Learning (EL; Authors, 2017).
EL shifts the focus from a particular type of activity (active learning), to the alignment among student learning outcomes, activities (including but not limited to active learning), and assessments. To do so, EL provides faculty with a process for designing and enacting high-quality courses that is modeled on an engineering design framework to provide familiar context for engineering faculty. Based on current educational research, EL focuses faculty on student learning and on designing learning experiences, rather than on “covering” content or texts. Through the design process, faculty consider the learning outcomes, assessments, students, and the tasks. It is within the design of the tasks that active learning is unpacked, developed, and selected to align with the learning outcomes.
The task design process in EL first focuses on the level of cognitive demand or depth of knowledge (Webb, 1997) of the learning outcome. Faculty then consider where the students might be at the start of the course and map tasks that scaffold and build students’ knowledge and skills to achieve the learning outcome. The focus on and mapping of the tasks shifts the lessons not only towards more active learning, but also towards particular active learning strategies that are well aligned to the learning outcomes. Students are organized and provided tasks to cognitively engage with the content through discourse, calculating, writing, analyzing, synthesizing, modeling, and other cognitively demanding tasks. We focus the depth of the demand using Webb’s Depth of Knowledge (Webb, 1997). The appropriateness of the task is evaluated by comparing the learning outcome depth and action verbs with those of the tasks.
This paper details the process of EL along with a case study that highlights how the process led to a more active learning course design. We also provide pair-wise data comparing results on common exams between the EL sections to other sections (not engineered) of the same course. The EL framework is further explored as a model to inform research and practices at other institutions.
Spiegel, S., & Sanders, M. (2018, March), Moving Beyond Active Learning to Engineering Learning: An Approach to Course Design and Enactment Paper presented at 2018 ASEE Zone IV Conference, Boulder, Colorado. https://peer.asee.org/29622
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