E-Learning Effectiveness in a Quantitative Course: Theoretical Versus Industry-Related Discussion and Exam Questions

E-Learning Effectiveness in a Quantitative Course: Theoretical Versus Industry-Related Discussion and Exam Questions

Kenneth David Strang (APPC Market Research, USA; State University of New York, USA; University of Technology, Australia)
DOI: 10.4018/jicte.2011040106
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Abstract

A quasi experiment compared the effectiveness of discussion question types on exam scores in an online quantitative methods course at an accredited university. Correlation, ANOVA and MANCOVA were utilized to test the hypothesis that questions exploiting industry examples would increase discussion interaction volume and exam scores more than using theoretical problems. Demographic factors (age, gender), semester timing, and prior ability were tested for moderation/mediation impact. Instructional method, professor, course content, assessment rubrics, and learning context were controlled. The treatment consisted of enhancing all discussion and examination questions from the materials and assessments to approximate authentic industry scenarios. A statistically significant model was validated, using exam question types as a factor, and a count of online discussion interactions (as a covariate), to measure problem-based learning effect on exam score.
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Introduction

Just as higher education practitioners are applying proven education psychology principles to Higher education practitioners are gradually transforming successful classroom teaching techniques into the online context. Learning Management Systems (LMS) allow educators to leverage communications technology to reach more students. Asynchronous discussion forums and synchronous interaction software (such as Skype) can be used to facilitate e-learning in place of the physical teaching context (Cox, Carr, & Hall, 2004). Modern technology is already being used in the workplace for virtual knowledge collaboration (Strang, 2008a, 2009a, 2010a; Strang & Chan, 2010) so it makes sense to encourage students to improve their online interaction skills. Certainly busy working students appreciate the convenience of online education (according to feedback). Nevertheless, teaching online courses effectively takes more effort as compared to the classroom (Evans et al., 2007).

Online quantitative (math-oriented) courses rely heavily on discussions and experiential exercises since interactive lectures and problem-based activities are challenging with online delivery modes. On average, quantitative subjects such as algebra, operations research, finance, and statistics are challenging in the classroom yet more difficult to learn online (Affouf & Walsh, 2007; Cybinski & Selvanathan, 2005; McCabe, 2007; Mills, 2004).

For this reason it is argued online discussions and problems in quantitative courses should be motivating and relevant so as to improve the e-learning experience and effectiveness. In particular, due to the volume and complexity of concepts in the materials, it is asserted that all lecture discussions and problem-based learning questions should apply relevant industry examples rather than theoretical exercises (leaving the text and videos to explain principles). Following this strategy, the way problems are phrased could impact e-learning outcomes.

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