The influence of narrative and expository lesson text structures on knowledge structures: alternate measures of knowledge structure

Clariana, Roy B.; Wolfe, Michael; Kim, Kyung

doi:10.1007/s11423-014-9348-3

Cited by 33 publications

(15 citation statements)

References 25 publications

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“…Each keyword may only be counted once toward this score. The links in common score compares the order of the keywords in the expert and student responses; a link is defined as two keywords appearing sequentially after all non-keywords are removed (see also Clariana, Wolfe, and Kim 2014).…”

Section: Graphical Interface For Knowledge Structure (Giks)mentioning

confidence: 99%

“…GIKS is unique in that it can provide specific feedback in the form of a visual representation of knowledge structure inherent in the text's key concepts (i.e., identified keywords) and their proximity relationships (i.e., distance between keywords). It has user buttons that change the display of the network graph to show errors only, correct associations only, and both; and that provides a list of missing terms and missing links and prompts the student to revise and resubmit their essay (e.g., Clariana, Wolfe, and Kim 2014;Fesel, Segers, Clariana, and Verhoeven 2015;Kim and Clariana 2015).…”

Section: Introductionmentioning

confidence: 99%

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Computer-Automated Approach for Scoring Short Essays in an Introductory Statistics Course

Zimmerman

Kang

Kim

et al. 2018

Journal of Statistics Education

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Over two semesters short essay prompts were developed for use with the Graphical Interface for Knowledge Structure (GIKS), an automated essay scoring system. Participants were students in an undergraduate-level online introductory statistics course. The GIKS compares students' writing samples with an expert's to produce keyword occurrence and links in common scores which can be used to construct a visual representation of an individual's knowledge structure. Each semester, students responded to the same two essay prompts during the first and last week of the course. All responses were scored by the GIKS and two instructors. Evidence for the validity of scores obtained using the GIKS was provided through the use of correlations with instructors' scores and final exam scores. Changes in scores from the beginning to end of the course were examined. Suggestions for writing open-ended prompts that work well with computer-automated scoring systems are given as well as suggestions for using the GIKS as a formative learning activity as opposed to summative assessment.

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Section: Graphical Interface For Knowledge Structure (Giks)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Computer-Automated Approach for Scoring Short Essays in an Introductory Statistics Course

Zimmerman

Kang

Kim

et al. 2018

Journal of Statistics Education

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“…Students regularly store knowledge as verbal representations (Clariana, Wolfe, & Kim, ) which can be retrieved in formats like a written response or oral explanation. Storing knowledge as a visual representation in addition to the verbal representation (i.e., dual coding), may enhance retrieval (Paivio, ) when it is advantageous for students to retrieve knowledge from both representations.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

Long-term conceptual retrieval by college biology majors following model-based instruction

Dauer

Long

2015

J Res Sci Teach

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One of the goals of college-level introductory biology is to establish a foundation of knowledge and skills that can be built upon throughout a biology curriculum. In a reformed introductory biology course, we used iterative model construction as a pedagogical tool to promote students' understanding about conceptual connections, particularly those linking genetic variation to organismal fitness. In interviews conducted 2.5 years later, we examined students' retrieval of conceptual connections emphasized during the course. Students constructed a model similar to those practiced during the course, reviewed their models with the interviewer, and answered questions about how they retrieved this knowledge conceptual understanding. Student proficiency on this task was evaluated based on the quality of their modeling and responses to questions about their models. Three distinct groups emerged: students that had an inadequate cognitive structure for the biological concepts (absent), and students that had incomplete or complete cognitive structures. Students in the Complete group were better able to verbally link genetic variation to phenotypic variation and differential fitness and successfully used relationships stored in their cognitive structure to explain gaps present in their drawn model. Students in the Incomplete group had fragmented knowledge where some concepts were connected to each other, but not to the whole model. Students in the Absent group had extensive gaps in knowledge and were unable to connect their conceptual ideas. Students who were most proficient in the task differed in their ability to access and search within their cognitive structure and verify the quality of their conceptual relationships. This allowed the most proficient students to fill in knowledge gaps and transfer their conceptual understanding to new contexts. © 2015 Wiley Periodicals, Inc. J Res Sci Teach 52: 1188-1206, 2015 Keywords: undergraduate; postsecondary; modeling; cognitive structure; genetics; evolution Retrieving knowledge from long-term memory is a cognitively intensive process consisting of global and local searches for relevant ideas and their verification. Knowing how a student in a classroom retrieves knowledge related to a discipline is essential for designing instruction that will effectively teach that knowledge.How students search for information related to course content might be best thought of through the following analogy-imagine opening your computer file manager (e.g., Windows Explorer or Apple Finder) and sorting by the date that files were modified or created, and locating

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“…As part of this process, practitioners and their peers apply their understanding of the problem and conceptual spaces to justify a viable solution (Hmelo-Silver, 2013). Over time, individuals use their peer networks to construct robust knowledge structures (KSs), which consist of the concepts and their relationships within a problem space (Clariana, Wolfe, & Kim, 2014; Jonassen, Beissner, & Yacci, 1993).…”

Section: Introductionmentioning

confidence: 99%

How Success Versus Failure Cases Support Knowledge Construction in Collaborative Problem-Solving

Tawfik

Kim

Hogan

et al. 2018

Journal of Educational Computing Research

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Theorists suggest that collaboration is a key aspect in online, inquiry-based learning. However, research finds that meaningful interaction is challenging, and learners struggle to sustain interaction. One way to scaffold collaborative problem-solving is through case libraries; however, few studies have explored how the type of experience depicted in a case library (success and failure) catalyzes learning. To address this gap, this study explored how the presence of success versus failure case libraries supports learning in terms of understanding of the problem space, conceptual space, knowledge construction convergence, and social network interaction. Results found no differences between conditions when discussing the problem space. However, results found that the failure group outperformed the success condition in terms of conceptual space, knowledge construction convergence, and social network interaction. As it relates to scaffolding using case-based reasoning theory and failure-driven memory theory, the failure cases helped to scaffold learners understanding of the broader conceptual space, knowledge construction, and learner–learner interaction. Additional implications for inquiry-based learning and scaffolding using case-based reasoning theory and failure-driven memory theory are provided.

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The influence of narrative and expository lesson text structures on knowledge structures: alternate measures of knowledge structure

Cited by 33 publications

References 25 publications

Computer-Automated Approach for Scoring Short Essays in an Introductory Statistics Course

Computer-Automated Approach for Scoring Short Essays in an Introductory Statistics Course

Long-term conceptual retrieval by college biology majors following model-based instruction

How Success Versus Failure Cases Support Knowledge Construction in Collaborative Problem-Solving

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