Evaluation of user Interface Design for Leaning Management System (LMS): Investigating Student's Eye Tracking Pattern and Experiences

Ramakrisnan, Prasanna; Jaafar, Azizah; Razak, Farizah Hanis Abdul; Ramba, Dianacamelia Anak

doi:10.1016/j.sbspro.2012.11.357

Cited by 37 publications

(18 citation statements)

References 8 publications

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“…For this analysis, eye movements present measures that can provide insights into the visual, cognitive and attentional aspects of human performance (Duchowski 2002). Pernice and Nielsen (2009) recommends at least 30 valid data subjects to get a stable heat map.…”

Section: Eye-tracking Metricsmentioning

confidence: 99%

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Zhu

Cao

et al. 2015

Cogn Tech Work

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This paper reports on an experimental study on human-machine interface in LED manufacturing systems to measure the influence of information overload on user experience. The results are based on cognitive ergonomics. The experiment used eye-tracking methods and a questionnaire to gather data. The independent variables were interface complexity and user background. Interface complexity had three levels: high interface complexity, moderate interface complexity and low interface complexity. User background had two levels: the novice group and the expert group. The dependent variables included time to first fixation, fixations before and subjective feelings. A total of 38 operators participated in the experiment, and the results showed that (1) interface complexity caused a significant difference in time to first fixation (P \ 0.05) and fixations before (P \ 0.05). Furthermore, the results revealed significant differences between high complexity interfaces compared to low complexity interfaces (P \ 0.05). However, no significant differences were observed between moderate and low complexity interfaces or between moderate and high complexity interfaces (P [ 0.05); (2) user background significantly affected the user experience; (3) within the same complexity level, expert operators' cognitive workload was significantly lower than that of novice operators; and (4) there was no significant relationship between the interface complexity and the user's background. The study concludes that because interface complexity has a significant effect on the time taken to locate the target button on the screen, interface design should be as simple as possible, while still providing the necessary level of functionality.

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Section: Eye-tracking Metricsmentioning

confidence: 99%

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Zhu

Cao

et al. 2015

Cogn Tech Work

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“…To provide more and better services, a Smart TV must have a menu system and UI that can be navigated to complete a task. As several researched have noted, an intuitive and easily navigated HCI and UI are critical to a good user experience of a Smart TV [1,9,13,18,21]. Hence, a comprehensive process that includes design and evaluation of Smart TV UIs is very important for making Smart TV services more desirable and useful .Unlike the features of a conventional TV with a remote control, new Smart TV features, such as web search, social networking, multi-user support, personalized services and application development, depend on innovative "natural" HCIs [4].…”

Section: A Services Design Methods For Develpoing Smart Tv Uismentioning

confidence: 99%

Integratring Service Design and Eye Teacking Insight for Designing Smart TV User Interfaces

Wang¹

2015

ijacsa

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Abstract-This research proposes a process that integrate service design method and eye tracking insight for designing a Smart TV user interface. The Service Design method, which is utilized for leading the combination of the quality function deployment (QFD) and the analytic hierarchy process (AHP), is used to analyze the features of three Smart TV user interface design mockups. Scientific evidences, which include the effectiveness and efficiency testing data obtained from eye tracking experiments with six participants, are provided the information for analysing the affordance of these design mockups. The results of this research demonstrate a comprehensive methodology that can be used iteratively for redesigning, redefining and evaluating of Smart TV user interfaces. It can also help to make the design of Smart TV user interfaces relate to users' behaviors and needs. So that to improve the affordance of design. Future studies may analyse the data that are derived from eye tracking experiments to improve our understanding of the spatial relationship between designed elements in a Smart TV user interface.

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“…In one study, Garrard (2014) reported that a high number of saccades indicates a long time to search for information, while a high number of fixations represents a high degree of user uncertainty. In a different study (Ramakrisnan, Jaafar, Razak, & Ramba, 2012), researchers evaluated the design of a learning management system (LMS) interface and highlighted the user's need for simplicity, memorability (e.g., how easy is it for the returning user to perform effectively), and control over the interaction with the LMS. The findings from these studies support Mele and Federici's (2012) idea that eyetracking is a "psychotechnology" because it emphasizes the intra-systemic perspective of the relationship between the user and the technology.…”

Section: Eye-tracking and User-centred Designmentioning

confidence: 99%

Gaze-Driven Design Insights to Amplify Debugging Skills: A Learner-Centered Analysis Approach

et al. 2018

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This study investigates how multimodal user-generated data can be used to reinforce learner reflection, improve teaching practices, and close the learning analytics loop. In particular, the aim of the study is to utilize user gaze and action-based data to examine the role of a mirroring tool (i.e., Exercise View in Eclipse) in orchestrating basic behavioural regulation during debugging. The results demonstrated that students who processed the information presented in the Exercise View and acted upon it, improved their performance and achieved a higher level of success than those who failed to do so. The findings shed light on what constitutes relevant data within a particular learning context in programming using gaze patterns. Moreover, these findings could guide the collection of essential learner-centred analytics for designing usable, modular learning environments based on data-driven approaches. Notes for Practice• Mirroring tools could regulate learner behaviour depending on the contextual set up of the programming environment.• This study demonstrated that students who improved their performance and achieved a higher level of debugging success have gaze patterns that corresponded with attention shifts with the mirroring tool and other areas of interest (AOIs).• Visual attention strategies among novices are not as well developed as they are among experts. This is shown in the successful and unsuccessful debugging behaviour patterns calculated from two-and three-way transition probabilities that we observed.• IDE-based (integrated development environment) learning analytics combined with gaze data could aid researchers and educators in designing and delivering interventions to enhance student progress by guiding them to attend to the right information at the right time so as to maximize student understanding of relevant concepts.

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Evaluation of user Interface Design for Leaning Management System (LMS): Investigating Student's Eye Tracking Pattern and Experiences

Cited by 37 publications

References 8 publications

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Influence of information overload on operator’s user experience of human–machine interface in LED manufacturing systems

Integratring Service Design and Eye Teacking Insight for Designing Smart TV User Interfaces

Gaze-Driven Design Insights to Amplify Debugging Skills: A Learner-Centered Analysis Approach

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