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Abstract Theories and practices to enhance multiple document comprehension and integration are crucial in both personal and work contexts, especially with the proliferation of printed and online sources. This experimental investigation replicates and extends (Wei et al., Educational Technology Research and Development 72:661–685, 2024) to examine how multiple documents integration is influenced by reading purpose, summary writing, and extra-textual networks (pre-reading, Study 1, and post-writing, Study 2). In Study 1 (N = 102), participants were randomly assigned to a pre-reading purpose set by a prompt (integrative or detailed) and by a network (an integrative or else an intra-text network) and then read three documents about Alzheimer’s disease to complete a writing task with revision (but no feedback). Three days later, they completed a delayed writing task and an inference verification test. In Study 2 (N = 90), the same procedure was used except that the network was used as feedback after writing to support revision. Results from the two studies agree with the previous research that the quantity and structural quality of integration can be improved by external cues and by delayed repeated writing. This research further confirms an innovative approach for evaluating different aspects of knowledge integration and contributes to the literature from the concept network perspective as a measure and an intervention of multiple-text reading.
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An OER Tool for Writing-to-Learn in Undergraduate STEM Courses
This “Listen and Learn” (Research paper) session demos an updated browser-based writing tool and then provides the 1st year data outcomes of a free open education resource (OER) called GIKS to provide STEM students with a teacher-made writing prompt that then scores the essay and displays it as a network to compare to an expert referent network.
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- Award ID(s):
- 2215807
- PAR ID:
- 10620776
- Publisher / Repository:
- International Society for Technology in Education (ISTE)
- Date Published:
- Format(s):
- Medium: X
- Location:
- ISTELive24 conference in Denver, CO, June 24-26, 2024
- Sponsoring Org:
- National Science Foundation
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Learning from multiple documents is an essential ability in today's society. This experimental study used concept network analysis to consider how reading prompts and post-reading generative learning tasks alter students' document integration performance. Undergraduates (N = 119) read three documents about Alzheimer's disease with one of two reading prompts (integrative purpose vs. detailed purpose) and then after reading completed a generative learning task (concept mapping vs. summary writing). Three days later they completed a delayed writing task and an inference verification test. Participants' written texts were converted to concept networks to evaluate conceptual level integration, including the quantity of integration (measured by the proportion of integrative links), the semantic quality of integration (measured by the similarity of integrative links), and the structural quality of integration (measured by comparing graph centrality). Results showed that the integrative purpose relative to the detailed purpose enhanced the quantity of integration but not the semantic and structural quality. Further, concept mapping relative to summary writing significantly improved the structural quality of integration. In addition, this study provides a new approach for evaluating different aspects of integration and contributes to multiple document comprehension literature from the perspective of concept network analysis.more » « less
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Smith, Bryan; Oskoz, A. (Ed.)Artificial intelligence (AI) for supporting second language (L2) writing processes and practices has garnered increasing interest in recent years, establishing AI-mediated L2 writing as a new norm for many multilingual classrooms. As such, the emergence of AI-mediated technologies has challenged L2 writing instructors and their philosophies regarding computer-assisted language learning (CALL) and teaching. Technologies that can combine principled pedagogical practices and the benefits of AI can help to change the landscape of L2 writing instruction while maintaining the integrity of knowledge production that is so important to CALL instructors. To align L2 instructional practices and CALL technologies, we discuss the development of an AI-mediated L2 writing technology that leverages genre-based instruction (GBI) and large language models to provide L2 writers and instructors with tools to enhance English for research publication purposes. Our work reports on the accuracy, precision, and recall of our network classification, which surpass previously reported research in the field of genre-based automated writing evaluation by offering a faster network training approach with higher accuracy of feedback provision and new beginnings for genre-based learning systems. Implications for tool development and GBI are discussed.more » « less
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Accepted Manuscript1.0
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