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The aim of this study was to investigate the role of visual/verbal cognitive style and interactivity level in dynamic and non-dynamic multimedia learning environments. A group of 235 biology students learned about photosynthesis either from a computer-based animation or a series of static pictures with spoken explanatory text. Participants were randomly assigned to one of two conditions: with or without the possibility to pause, to play, or to fast-forward/rewind the learning environment (self-paced versus system-paced condition). Participants obtained better results when learning with the system-paced environment than with the self-paced one. A significant triple interaction between cognitive style, type of pacing, and type of visualization showed that highly developed visualizers learned poorer with self-paced static pictures than with system-paced static pictures. There were no significant effects regarding verbal cognitive style. Results shed more light on the relation between different levels of interactivity and visual cognitive style, when learning from static pictures. (ZPID).

Interactive 3D visualizations of geospatial data are currently available and popular through various applications such as Google EarthTM and others. Several studies have focused on user performance with 3D maps, but static 3D maps were mostly used as stimuli. The main objective of this paper was to identify differences between interactive and static 3D maps. We also explored the role of different tasks and inter-individual differences of map users. In the experimental study, we analyzed effectiveness, efficiency, and subjective preferences, when working with static and interactive 3D maps. The study included 76 participants and used a within-subjects design. Experimental testing was performed using our own testing tool 3DmoveR 2.0, which was based on a user logging method and open web technologies. We demonstrated statistically significant differences between interactive and static 3D maps in effectiveness, efficiency, and subjective preferences. Interactivity influenced the results mainly in ‘spatial understanding’ and ‘combined’ tasks. From the identified differences, we concluded that the results of the user studies with static 3D maps as stimuli could not be transferred to interactive 3D visualizations or virtual reality.

The purpose of this study was to examine the instructional relationship between the cognitive level of adjunct question type (fact vs. comprehension) and the type of student interactivity (Type 1: Associative processing with simple-click activity vs. Type 2: Associative and referential processing with drag-drop activity) on tests measuring different instructional objectives. 106 undergraduate students were randomly assigned to four treatment groups. Immediately after interacting with their respective instructive materials they completed three individual criterion measures. Data was analyzed via a 2x2 ANOVA. Item analysis was used to design and position questions in the instructional unit where students experienced difficulty in acquiring the designated content being assessed by the criterion measures. Analysis of the data indicated that an insignificant interaction existed between cognitive levels of the questions and interaction type on each of the criterion measures. There was a significant main effect with the type 2 treatment achieving significantly higher scores than the type 1 treatment on both the identification/terminology and comprehension criterion measures for both types of questions (fact and comprehension). Results obtained in this study indicate that not all types of interactivity are equally effective in facilitating acquirement of different types of educational objectives and that insignificant differences in treatment were found to exist between the cognitive level of questions on the different criterion measures.

During the past decade, the Internet has established itself as a powerful medium that has revolutionized the way people do business. Thousands of companies are increasingly realizing the tremendous capability of the World Wide Web as a selling channel and, consequently, integrating e-business into their business models. Like businesses across all industries, hotels are adapting to this new environment and working vigorously to use web sites to communicate directly with travelers and offer customers the ability to search information and book an entire trip online. Recent research suggests that one of the key elements in a successful commercial web site is its design; the success or failure of any particular business is based in large part on the quality of the design of the company’s web site. One of the most important design elements in commercial web sites may be their interactivity. As a critical concept in computer-mediated communications, the interactivity of a web site is known to be a key motivation of consumers’ use of the Internet, an important determinant of web site quality, and one that leads to a positive attitude toward the site. Despite its value, little is understood about the nature and role of interactivity on hotel web sites and its impact on travelers’ attitudes and behaviors. However, studies that provide insight into the strengths, facets, potential, and influences of the interactivity of hotel web sites were not found. In the present study, the researcher examined if the increased level of interactivity of a web site had positive effects on the web users’ attitudes, behaviors, and experience online in the context of hotel web sites, a crucial point of debate among researchers and an assumption that is inconclusive, contradictory, and inconsistent in the extant literature. The researcher also examined the consequences of actual user-site interactivity, specifically how actual user-site interactivity, i.e., from a behavioral perspective rather than an intentional perspective, influences web users’ attitudes and behaviors toward web sites. Last, the researcher examined if there was an interaction effect of the level of feature-based interactivity and actual user-site interactivity on the users’ perceived quality of the site, attitude toward the site, attitude toward the brand, perceived interactivity of the site, intention to revisit and recommend the site to others, and overall experience online. While building on and maintaining sustainability with extant work, a conceptual model was developed to examine feature-based interactivity and actual user-site interactivity as two important determinants of Web users’ perceptions, attitudes, behavioral intentions, and overall experience online in the context of hotel web sites. A computer-based experimental study was conducted with nine Jamaican hotel web sites in which feature-based interactivity varied at three levels: low, medium, and high. These web sites were evaluated by 137 participants in order to identify how the level of feature-based interactivity of a web site impacts actual user-site interactivity, and how both variables influence web participants’ attitudes, behaviors, and experiences online. The techniques for the data analysis included descriptive statistics, correlation analysis, independent-samples, t tests, one-way ANOVA, and multiple regression analysis. The results of these analyses indicated that the higher the level of feature-based interactivity of a web site, the greater the participants’ perceived quality of the site, attitude toward the site, attitude toward the brand, perceived interactivity of the site, intention to revisit and recommend the site to others, and overall experience online was supported. Additionally, results indicated that a high degree of user interactivity with a site did yield a more favorable attitude and behavior online. Last, there was a significant main effect of perceived quality of the web site, attitude toward the web site, brand attitude, and perceived interactivity of the web site on the participants’ overall experience online, intention to revisit the web site, and intention to recommend the web site to others.

Educational researchers have been confronted with a multitude of definitions of task complexity and a lack of consensus on how to measure it. Using a cognitive load theory-based perspective, we argue that the task complexity that learners experience is based on element interactivity. Element interactivity can be determined by simultaneously considering the structure of the information being processed and the knowledge held in long-term memory of the person processing the information. Although the structure of information in a learning task can easily be quantified by counting the number of interacting information elements, knowledge held in long-term memory can only be estimated using teacher judgment or knowledge tests. In this paper, we describe the different perspectives on task complexity and present some concrete examples from cognitive load research on how to estimate the levels of element interactivity determining intrinsic and extraneous cognitive load. The theoretical and practical implications of the cognitive load perspective of task complexity for instructional design are discussed.

Within the framework of cognitive load theory, the element interactivity and the expertise reversal effects usually are not treated as closely related effects. We argue that the two effects may be intertwined with the expertise reversal effect constituting a particular example of the element interactivity effect. Specifically, the element interactivity effect relies on changes in element interactivity due to changes in the type of material being learned, while the expertise reversal effect also relies on changes in relative levels of element interactivity but in this case, due to changes in relative levels of expertise. If so, both effects rely on equivalent changes in element interactivity with the changes induced by different factors. Empirical evidence is used to support this contention.

In cognitive load theory, element interactivity has been used as the basic, defining mechanism of intrinsic cognitive load for many years. In this article, it is suggested that element interactivity underlies extraneous cognitive load as well. By defining extraneous cognitive load in terms of element interactivity, a distinct relation between intrinsic and extraneous cognitive load can be established based on whether element interactivity is essential to the task at hand or whether it is a function of instructional procedures. Furthermore, germane cognitive load can be defined in terms of intrinsic cognitive load, thus also associating germane cognitive load with element interactivity. An analysis of the consequences of explaining the various cognitive load effects in terms of element interactivity is carried out.

The segmenting effect states that people learn better when multimedia instructions are presented in (meaningful and coherent) learner-paced segments, rather than as continuous units. This meta-analysis contains 56 investigations including 88 pairwise comparisons and reveals a significant segmenting effect with small to medium effects for retention and transfer performance. Segmentation also reduces the overall cognitive load and increases learning time. These four effects are confirmed for a system-paced segmentation. The meta-analysis tests different explanations for the segmenting effect that concern facilitating chunking and structuring due to segmenting the multimedia instruction by the instructional designer, providing more time for processing the instruction and allowing the learners to adapt the presentation pace to their individual needs. Moderation analyses indicate that learners with high prior knowledge benefitted more from segmenting instructional material than learners with no or low prior knowledge in terms of retention performance.

The concept of productive failure posits that a problem-solving phase prior to explicit instruction is more effective than explicit instruction followed by problem-solving. This prediction was tested with Year 5 primary school students learning about light energy efficiency. Two, fully randomised, controlled experiments were conducted. In the first experiment ( N  = 64), explicit instruction followed by problem-solving was found to be superior to the reverse order for performance on problems similar to those used during instruction, with no difference on transfer problems. In the second experiment, where element interactivity was increased ( N  = 71), explicit instruction followed by problem-solving was found to be superior to the reverse order for performance on both similar and transfer problems. The contradictory predictions and results of a productive failure approach and cognitive load theory are discussed using the concept of element interactivity. Specifically, for learning where element interactivity is high, explicit instruction should precede problem-solving.

Van Gog and Sweller (2015) claim that there is no testing effect—no benefit of practicing retrieval—for complex materials. We show that this claim is incorrect on several grounds. First, Van Gog and Sweller's idea of \"element interactivity\" is not defined in a quantitative, measurable way. As a consequence, the idea is applied inconsistently in their literature review. Second, none of the experiments on retrieval practice with worked-example materials manipulated element interactivity. Third, Van Gog and Sweller's literature review omitted several studies that have shown retrieval practice effects with complex materials, including studies that directly manipulated the complexity of the materials. Fourth, the experiments that did not show retrieval practice effects, which were emphasized by Van Gog and Sweller, either involved retrieval of isolated words in individual sentences or required immediate, massed retrieval practice. The experiments failed to observe retrieval practice effects because of the retrieval tasks, not because of the complexity of the materials. Finally, even though the worked-example experiments emphasized by Van Gog and Sweller have methodological problems, they do not show strong evidence favoring the null. Instead, the data provide evidence that there is indeed a small positive effect of retrieval practice with worked examples. Retrieval practice remains an effective way to improve meaningful learning of complex materials.