4.7 Article

A case study of undergraduate engineering students' computational literacy and self-beliefs about computing in the context of authentic practices

Journal

COMPUTERS IN HUMAN BEHAVIOR
Volume 61, Issue -, Pages 427-442

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chb.2016.03.025

Keywords

Computational literacy; Self-beliefs; Modeling and simulation practices; Anchored instruction

Funding

  1. U.S. National Science Foundation [EEC1137006, EEC1329262, EEC1449238]
  2. Div Of Engineering Education and Centers
  3. Directorate For Engineering [1449238, 1329262] Funding Source: National Science Foundation

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Engineering students, as compared to computing-related majors, are not traditionally introduced to computing in the context of authentic learning experiences, i.e., real-world applications within their discipline. This paper identifies the impact of computation delivered by authentic learning experiences in the form of anchored instruction on students' self-beliefs and their capacity to leverage computation to acquire disciplinary concepts in subsequent computationally-based engineering coursework. This case study included 130 students with different programing preparation (authentic or traditional), who were exposed to computational learning modules. Control-Value Theory of Achievement Emotions is the conceptual framework that guided the evaluation of this investigation. Measures included student self beliefs such as control and value appraisals, and their relationship with academic performance. Results suggest that programming preparation presented in an authentic engineering context provides an important foundation that goes beyond increasing students' control self-beliefs. This preparation seems to effectively enable students to leverage computational practices for the purpose of acquiring disciplinary concepts. Implications for teaching relate to the integration of computation sooner, more often and within a disciplinary context in the undergraduate engineering curriculum. Implications for learning relate to fostering engineering computational literacy guided by anchored instruction to support disciplinary problem solving. (C) 2016 Elsevier Ltd. All rights reserved.

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