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How does the conceptual structure of external representations contribute to learning? This investigation considered the influence of generative concept sorting (Study 1, n=58) and of external structure information (Study 2, n=120) moderated by perceived difficulty. In Study 1, undergraduate students completed a perceived difficulty survey and comprehension pretest, then a sorting task, and finally a comprehension posttest. Results showed that both perceived difficulty and comprehension pretest significantly predicted comprehension posttest performance. Learners who perceived that history is difficult attained significantly greater posttest scores and had more expert-like networks. In Study 2, participants completed the perceived difficulty survey and comprehension pretest, then read a text with different external structure support, either an expert network or an equivalent outline of the text, and finally completed a sorting task posttest and a comprehension posttest. In study 2, there was no significant difference for external structure support on posttest comprehension (outline = network), but reading with an outline led to a linear topic order conceptual structure of the text, while reading with a network led a more expert-like relational structure. As in Study 1, comprehension pretest and perceived difficulty significantly predicted posttest performance, but in contrast to Study 1, learners who perceived that history is easy attained significantly greater posttest scores. For theory building purposes, post-reading mental representations matched the form of the external representation used when reading. Practitioners should consider using generative sorting tasks when relearning history content.
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Net.Create: Network Analysis in Collaborative Co-Construction of Historical Context in a Large Undergraduate Classroom
History educators in large-lecture humanities undergraduate classrooms struggle to support reading comprehension, defined as the ability to simultaneously read a complex text critically, understand the text’s details and context, and vet the text’s claims. Critical reading of historical texts in particular helps bridge the gap between seeing history as memorization-oriented and seeing it as an inquiry-oriented discipline that reconstructs narrative and context. Net.Create is an open-source, network-analysis software tool paired with activities that support intuitive creation and revision of a network data set and accompanying visualization, and through these representational practices, reading comprehension in humanities classrooms. Findings show that as students draw on details in a historical text to collaboratively construct a larger network, they begin to emphasize context reconstruction over memorization.
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- Award ID(s):
- 1848655
- PAR ID:
- 10300994
- Editor(s):
- Gresalfi, M. and
- Date Published:
- Journal Name:
- The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020
- Volume:
- 2
- Page Range / eLocation ID:
- 1055-1062
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/https://repository.isls.org//handle/1/6293
