Robert Schulz

Cognitive Learning Styles and Academic Performance in Two Postsecondary Computer Application Courses

Abstract This study investigated the effects of cognitive learning style on academic performance in two university-level computer applications courses offered by the Faculty of Education and the Department of Computer Science at a large urban university. The Gregorc Style Delineator (Gregorc, 1982a) was used to collect learning-style information from a sample of 974 students over a four-year period from 1993 to 1997. The effect of learning style on academic performance was found to be significant in both courses. Results indicated that sequential learners performed significantly better than did random learners in both courses under investigation. Based on the results, a number of recommendations are made for how instructors can accommodate the needs of all learning styles when facilitating computer application courses.

Cognitive Learning Styles and Academic Performance in 19 First-Year University Courses: Successful Students Versus Students at Risk

This study investigated the effects of cognitive learning style on 1st-year academic performance in 19 university courses. The Gregorc Style Delineator was used to collect learning style information from a sample of 4,546 students over a 4-year period from 1993 to 1997. Academic performance based on learning style was found to be significant (p < 0.05) in 11 of the 19 courses. Based on chi-square and analysis of variance results, it would appear that science and math-related fields are better suited to learners who think sequentially; random learners excel in fine arts courses. All learning styles perform equally well in the liberal arts and social sciences. Implications of the study are discussed.

The Drivers of Corporate Climate Change Strategies and Public Policy A New Resource-Based View Perspective

Effective public policy to mitigate climate change footprints should build on data-driven analysis of firm-level strategies. This article’s conceptual approach augments the resource-based view (RBV) of the firm and identifies investments in four firm-level resource domains (Governance, Information management, Systems, and Technology [GISTe]) to develop capabilities in climate change impact mitigation. The authors denote the resulting framework as the GISTe model, which frames their analysis and public policy recommendations. This research uses the 2008 Carbon Disclosure Project (CDP) database, with high-quality information on firm-level climate change strategies for 552 companies from North America and Europe. In contrast to the widely accepted myth that European firms are performing better than North American ones, the authors find a different result. Many firms, whether European or North American, do not just “talk” about climate change impact mitigation, but actually do “walk the talk.” European firms appear to be better than their North American counterparts in “walk I,” denoting attention to governance, information management, and systems. But when it comes down to “walk II,” meaning actual Technology-related investments, North American firms’ performance is equal or superior to that of the European companies. The authors formulate public policy recommendations to accelerate firm-level, sector-level, and cluster-level implementation of climate change strategies.