دانلود رایگان مقاله مقایسه سیب و پرتقال؟ پژوهش در آموزش استاتیک در مقابل انیمیشن

Abstract

Many of the studies that have compared the instructional effectiveness of static with dynamic images have not controlled all the moderating variables involved. This problem is present not only in instructional pictures concerning the curricular topics (e.g., science, technology, engineering and mathematics: STEM), but also in those depicting extracurricular tasks (e.g., human movement tasks). When factors such as appeal, media, realism, size, and interaction are not tightly controlled between statics and animations, researchers may often be comparing apples with oranges. In this review, we provide a categorization of these confounding variables and offer some possible solutions to generate more tightly controlled studies. Future research could consider these biases and solutions, in order to design more equivalent visualizations. As a result, more conclusive evidence could be obtained identifying the boundary conditions for when static or dynamic images are more suitable for educational purposes, across both curricular and extracurricular tasks.

4. Discussion

Despite a long research tradition investigating the educational effectiveness of both static and dynamic pictures, their relative instructional importance may be difficult to assess. One key factor to consider when comparing both visualizations is the instructional task at stake: our evolved mind seems to be more suited to learn animated primary tasks and static secondary tasks. However, clear conclusions are not easy to draw, yet, as many of the studies comparing static and animated formats (for both primary and secondary tasks) have presented uncontrolled biases. We discussed appeal, variety, media, realism, number, size, and interaction biases as example of seven confounding variables. Over a decade ago, Tversky et al. (2002) observed that biases in comparisons between static and dynamic images existed. Our review indicates that researchers are still designing experiments that contain them, and thus to some extent ignoring the messages inherent in the review by Tversky and colleagues. For example, we reported two meta-analyses (Berney & Betrancourt, 2016; H of € fler & Leutner, 2007) that included several of the studies included here (e.g., Lewalter, 2003; Mayer et al., 2005; Ryoo & Linn, 2012; Wu & Chiang, 2013; Yang et al., 2003) that did not control these bias factors, which suggests some loss of validity. Clearly much greater attention to biases is needed into future meta-analyses as well as individual studies to take the field forward. We believe that the present review, categorizing and giving examples of these problematic current comparisons, was necessary to re-emphasize the original message of Tversky et al. (2002). In addition, we adopted a practical approach by providing guidelines for avoiding and controlling these problems in future investigations.