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Individual Differences and Inclusive Design
Published in Constantine Stephanidis, User Interfaces for All, 2000
David Benyon, Alison Crerar, Simon Wilkinson
A distinction is commonly made in the HCI literature between novice and expert users, the supposition often being that experts or “power users” are faster, more accurate, and more sophisticated in their use of a system. Interestingly, in the context of office-related tasks, Prümper, Zapf, Brodbeck, and Frese (1992) found that novices and experts did not make a significantly different number of mistakes, although, as expected, the experts recovered from their errors more quickly. However, a difference in the type of errors was observed: Experts were found to make fewer mistakes resulting from a lack of system knowledge, but instead experienced more functionality problems. In a separate study, Kalyuga, Chandler and Sweller (1998) found that, as subjects’ expertise changed, so did the interface that was most efficient for them. Although the study investigated differences in expertise and the design of instructional materials, it should have implications for noneducational systems as well. The main finding was that novice subjects preferred diagrams that physically integrated text and graphics, whereas experts were more efficient with graphical diagrams with the text eliminated. The authors suggested that the reason for this can be explained in terms of the split-attention effect and the redundancy effect. The split-attention effect is caused by multiple sources of information that need to be combined in order to be understandable (e.g., topographical map plus key). The mental process of integration is cognitively demanding and can be helped by the physical integration of information in the stimulus material (placing text within the map/diagram). This was found by Kalyuga et al. to help novice subjects. However, when an individual gains expertise, the redundancy effect is more likely. This happens when redundant information is presented (e.g., diagram plus text describing the diagram), which causes unnecessary cognitive load. In this situation, the experts benefited more from a diagram that showed graphics only.
Instructor’s position affects learning from video lectures in Chinese context: an eye-tracking study
Published in Behaviour & Information Technology, 2022
Yi Zhang, Ke Xu, Zhongling Pi, Jiumin Yang
It is worth noting that the eye movement data also revealed that compared to students in the left and right conditions, those in the middle condition paid less attention to the learning content area and made more switches between the instructor and learning content. This is consistent with previous studies of visual processing habits, in which processing occurs from left to right, with most time spent in the middle (Cao et al. 2013; Jiang et al. 2016). That is, in this study, when the instructor was in the middle of the screen there was a split attention effect, and this effect seemed to be unfavourable for learning. However, this kind of video lecture is actually used in real settings, and there may be some settings in which this video lecture design may be beneficial. For example, it might be helpful to have the instructor in the middle of the screen when the learning content is closely related to the instructor, such as second language learning (Kushch, Igualada, and Prieto 2018). It may also be helpful when instructors use a transparent whiteboard (Fiorella et al. 2019; Stull et al. 2018a), which requires students to capture the instructor’s mouth, eye gaze and hand drawing. In these cases having the instructor in the middle might be beneficial for learning because it will attract more attention from the students.
An eye-tracking paradigm to explore the effect of online consumers’ emotion on their visual behaviour between desktop screen and mobile screen
Published in Behaviour & Information Technology, 2022
In HCI research fields, the different visual behaviour between desktop computer and mobile device was also discussed in terms of user’s cognitive information processing from different screen size and information search feature (Chae and Kim 2004; Harrison and Dey 2008). The small screen size of a mobile device, compared with that of a desktop computer, means that a limited amount of information can be displayed (Byrd and Caldwell 2011). Small screen displays require a breach in the spatial and temporal contiguity of the information presented. This split attention effect associated with the restricted view of small screens can cause information chunking, such that users lose a global perspective of the task and thereby incur a higher cognitive load (Keefe et al. 2012). Small screens cause overload by cutting off information and also force participants to scroll and navigate through ill-defined chunks of content (Ng and Nicholas 2009). Thus, users will experience a heavier cognitive load from the visual complexity on a mobile screen. The intricate information structure displayed on the small screen of a non-touch mobile phone, combined with the increasing visual complexity of mobile tasks, leads to a serious obstacle in the functionality of mobile devices (Byrd and Caldwell 2011).
Interactive Instruction in Bayesian Inference
Published in Human–Computer Interaction, 2018
Azam Khan, Simon Breslav, Kasper Hornbæk
Poor layout can also cause extraneous processing in participants. When captions or labels are not placed together with the object to which they apply, a split-attention effect occurs, as the participant must attend to both locations and conceptually integrate the presentation. In the double-tree diagram (see Figure 6) that we employed in both static and interactive experimental conditions, we placed the labels inside boxes representing the nodes in the tree. In this way, the labels were always with the node to which they refer, avoiding the typical arrow pointing from a displaced label to a part of the diagram.