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Abstract Background Coding has become an integral part of STEM education. However, novice learners face difficulties in processing codes within embedded structures (also termed nested structures). This study aimed to investigate the cognitive mechanism underlying the processing of embedded coding structures based on hierarchical complexity theory, which suggests that more complex hierarchies are involved in embedded versus sequential coding structures. Hierarchical processing is expected to place a great load on the working memory system to maintain, update, and manipulate information. We therefore examined the difference in cognitive load induced by embedded versus sequential structures, and the relations between the difference in cognitive load and working memory capacity. Results The results of Experiment 1 did not fully support our hypotheses, possibly due to the unexpected use of cognitive strategies and the way stimuli were presented. With these factors well controlled, a new paradigm was designed in Experiment 2. Results indicate that the cognitive load, as measured by the accuracy and response times of a code comprehension task, was greater in embedded versus sequential conditions. Additionally, the extra cognitive load induced by embedded coding structures was significantly related to working memory capacity. Conclusions The findings of these analyses suggest that processing embedded coding structures exerts great demands on the working memory system to maintain and manipulate hierarchical information. It is therefore important to provide scaffolding strategies to help novice learners process codes across different hierarchical levels within embedded coding structures.

Metaphors are well-known tools for teaching statistics to novices. However, educators might overlook metaphor theoretical developments that offer nuanced and testable perspectives on their pedagogical applications. This article introduces the notion of metaphor types—“correspondence” (CO) and “class inclusion” (CI)—as different strategic ways of presenting metaphors and reports an experimental study on their effectiveness in teaching basic regression to language and communication majors. Briefly, CO emphasizes systematic links while CI emphasizes holistic perceptions of similarity between the source and target of a metaphor. Both competency and attitudinal measures were compared in view of the latter’s importance as intended outcomes of the typical introductory course. The results show that while CO outperformed CI in assessments of manual calculations (e.g., SST/SSR/SSE/R2), CI outperformed CO in essay assessments requiring elaboration of general conceptual understanding. CI was also linked to more positive perceptions of the practical utility of regression analysis and its contribution to personal growth. Correlations between performance and attitudes were stronger in CO than CI, which further suggests CO’s greater perceived resemblance to a “rote learning” approach. The attendant implications are discussed in the growing context of general statistics education for nonstatistics majors. Directions for further research are suggested.

Emergent learning describes learning that occurs when participants interact and distribute knowledge, where learning is self-directed, and where the learning destination of the participants is largely unpredictable (Williams, Karousou, & Mackness, 2011). These notions of learning arise from the topologies of social networks and can be applied to the learning that occurs in educational institutions. However, the question remains whether institutional frameworks can accommodate the opposing notion of “cooperative systems” (Shirky, 2005), systems that facilitate the creation of user-generated content, particularly as first-year education cohorts are novice groups in the sense of not yet having developed university-level knowledge. This paper theorizes an emergent learning assessment item (Flickr photo-narratives) within a first-year media arts undergraduate education course. It challenges the conventional models of student–lecturer interaction by outlining a methodology of teaching for emergence that will facilitate student-directed and open-ended learning. The paper applies a matrix with four parameters (teacher-directed content/student-directed content; non-interactive learning task/interactive learning framework). This matrix is used as a conceptual space within which to investigate how a learning task might be constructed to afford the best opportunities for emergent learning. It explores the strategies that interactive artists utilize for participant engagement (particularly the relationship between the artist and the audience in the creation of interactive artworks) and suggests how these strategies might be applied to emergent generative outcomes with first-year education students. We build upon Williams et al.’s framework of emergent learning, where “content will not be delivered to learners but co-constructed with them” (De Freitas & Conole, as cited in Williams et al., 2011, p. 40), and the notion that in constructing emergent learning environments “considerable effort is required to ensure an effective balance between openness and constraint” (Williams et al., 2011, p. 39). We assert that for a learning event within a Web 2.0 environment to be considered emergent, not only does there need to be an effective balance between teacher-directed content and student-directed content for knowledge to be open, creative, and distributed by learners (Williams et al., 2011), but there also need to be multiple opportunities for interaction and communication between students within the system and that these “drive the emergence of structures that are more complex than the mere parts of that system” (Sommerer & Mignonneau, 2002, p. 161).