Addressing Diverse College Students and Interdisciplinary Learning Experiences Through Online Virtual Laboratory Instruction: A Theoretical Approach to Error-Based Learning in Biopsychology

Addressing Diverse College Students and Interdisciplinary Learning Experiences Through Online Virtual Laboratory Instruction: A Theoretical Approach to Error-Based Learning in Biopsychology

Lorenz S. Neuwirth (SUNY Old Westbury, USA), Alireza Ebrahimi (SUNY Old Westbury, USA), B. Runi Mukherji (SUNY Old Westbury, USA) and Lillian Park (SUNY Old Westbury, USA)
DOI: 10.4018/978-1-5225-5332-8.ch012
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Abstract

Habits in note-taking and media usage of the current generation of undergraduate college students are very different from prior generations. Current students are attracted to multi-dimensional teaching approaches which utilize visual learning aids and increased social interactions beyond the traditional lecture. Moreover, the diversity with respect to first generation college student/immigrant and returning learners is growing. This learning situation becomes further complicated in teaching interdisciplinary biopsychology courses, where students may not possess a complete set of foundational concepts. Thus, students require increased learning opportunities, sustained practice, as well as positive and corrective feedback to meet curricular proficiency expectations. At the same time, many students also have difficulty receiving, accepting, and implementing necessary feedback in order to succeed in their academic endeavors. To address this “feedback” issue, we have proposed a theoretical approach using “error-based” learning, for a biopsychology curriculum, to remedy this student learning problem through virtual laboratory instruction. Notably, this approach can be used in other integrative fields of learning.
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Background

Maseleno, Hardaker, Sabani & Suhaili (2016) offered a unique perspective to address the academic achievement gap. They posited a multi-cultural education model, characterizing students culture, learning styles (i.e., preferences and cognitive framework), and creativity in order to develop a software diagnostic tool to target their needs for intervention (i.e., learner analytics and predictive modeling). Their study employed a questionnaire that analyzed student’s learning patterns: culture through race, ethnicity, language; learning preferences through physiological and perceptual domains; cognitive learning styles through physical, mental, and emotional approaches; and creativity through problem solving skills, motivation, and subject specific knowledge (Maseleno et al, 2016). The study concluded, based on their dataset that creativity was at the core of their predictive analytic model for multi-cultural student education. However, the study failed to elaborate on specific instructional and curricular interventions that could be utilized by educators to address the academic achievement gap. Moreover, research in this area is both timely and necessary to understand and address student-specific needs and further to facilitate faculty efforts to intervene effectively.

It is important to note that culture in the Maseleno et al. (2016) study referred to students’ own background(s), i.e., the context in which their learning history was established, which often was their Country of Origin’s Educational Context, as well as the background(s) of others, i.e., the new context in which their learning history is now being challenged (the American Educational Context). In our approach we agree to some extent with the learner analytics and predictive modeling of Maseleno et al. (2016) that was adapted from Amabile (1997). However, we caution the assumption that creativity is the core factor, or necessarily the most appropriate attribute for characterizing the learner (for more details, see Maseleno et al., 2016), since such contributing factors are likely to be nonlinear (i.e., one factor does not relate equally and build sequentially from another).

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