The impact of animation interactivity on novices’ learning of introductory statistics

Abstract

and their never-ending supports. This study was a one-way design where the independent variable was animation interactivity. In addition to a control group (Static Group) provided with only static materials, there were three groups with different levels of animation interactivity: 1) Animation with simple interactivity (Simple Animation Group), 2) animation with input vii manipulation (Input Group), and 3) animation with practice and feedback (Practice Group). A sample of 123 college students participated in the study and was randomly assigned into groups. They gathered in the computer lab to work with the animation program and then took online surveys and tests for evaluation. Students were expected to learn Principles of Hypothesis Testing (concepts of type I error, type II error and pvalue). The data collected in this study included 1) student learning attitudes, 2) achievement and confidence pre-test scores, 3) achievement and confidence post-test scores, and 4) program perception. Also, student manipulation of the animation program was recorded as Web log data. The data were analyzed by using multivariate analysis (MANOVA), univariate analysis (ANOVA), regression analysis, regression tree analysis and case analysis.The findings were as follows: 1) Animation interactivity impacted students' improvement in understanding (p=.006) and lower-level applying (p=.042), 2) animation interactivity did not impact student confidence and program perception, 3) the regression analysis indicated that student prior knowledge and interest were the most important predictors on student achievement post-test scores instead of program manipulation, and 4) the regression tree showed that there were interactions among student interest, prior knowledge, and program manipulation on the achievement post-test scores. The case analysis showed that not all students manipulated the interactive animation program as expected due to a lack of motivation and cognitive skills, and this could decrease the effect of the interactive animation. This study hoped to broaden theories on interactive learning and serve as a reference for future statistics curriculum designers and textbook publishers.viii He asked students to first clarify the definition of the type I and type II error, and then look for clues in the question for computation. The type I and type II error problems are difficult for most novice learners. But with the concrete examples of "bags," "boxes," List of Tablesor "envelopes," statistics was no longer as difficult for me. This particular teaching method is valuable for use in all introductory-level classes. 3I believe this struggle with learning statistics is not limited to myself, but is common to many other students. As a result, I created an online animated program based on my instructor's teaching method in order to help learners who also struggle with learning type I error, type II error and the p-value. This online animation was created to popularize this particular teaching method. To benefit learners with different ...

Does animation enhance learning? A meta-analysis

“…Gagne's taxonomy (1982) was mentioned by Rieber (1989Rieber ( , 1991, and Bloom's taxonomy (1956) was mentioned by Rigney (1976). Wang, Vaughn, and Liu (2011) referred to the revised taxonomy of Bloom (Anderson & Krathwohl, 2001). Recoding the initial learning outcomes with the BTr (Anderson & Krathwohl, 2001) has reduced the number of outcomes variates from 13 to 8, as can be seen in Table 1.…”

Comparing apples and oranges? A critical look at research on learning from statics versus animations

“…A C C E P T E D format size (e.g., Schnotz & Lowe, 2008), and level of interaction (e.g., Wang et al, 2011) can impact significantly on learning from visualizations. As such, biased comparisons that do not control these factors may lead to incorrect educational interpretations.…”

“…However, a full interactive animation, which also included the primary interactions of dragging and controlling the topographic instrument, was the most effective. Similarly, in the study with engineers given a Lego truck to disassembly,Akinlofa et al (2013, see Section 3.2) observed that the most effective learning condition was the interactive virtual space, where participants could drag the computer replicas of the Lego This primary interactive display was a better instructional format than two simpler secondary interactive visualizations (static pictures and video), where the users could only change the presentations' pace.Because interactive features can help understanding STEM concepts (e.g.,Wang, Vaughn, & Liu, 2011; but seePedra, Mayer, & Albertin, 2015), they must be controlled in unbiased static versus animation comparisons. However, sometimes statics cannot include as many interactive facilities as animations (seeTversky et al, 2002), which may limit the scope of research that can be conducted linking interaction with presentation types.…”

E-Learning as a Stimulation Methodology to Undergraduate Engineering Students

“…As a matter of fact, using animations has a significant impact on the students' understanding especially for sophisticated courses which need a tremendous amount of imagination by using basic animation techniques in PowerPoint presentations which provides an additional learning aid that support learning [1]. Moreover, it is suggested that increasing animation interactivity could significantly enhance students' achievement and improvement at the intermediate level of learning, in addition students confidence improvement and perception were not significantly impacted by the increase of animation interactivity [7]. It is well known that video tutorials are not a new concept [2] emerging in the late 1960s, since then, video modeling has been described as "instructional videos" or "video tutorials."…”