![]() In this paper, we investigate the learning effectiveness of a tool-mediated learning activity to support instruction of established human performance models, namely the Keystroke Level Model (KLM) and Fitts’ law, and their application in web form design practice. However, the error rate for the third custom-built Android app was 40.0%, indicating that additional steps are required to finetune the FLM-2A predictions.Įffective teaching of concepts related to human computer interaction (HCI) requires introduction of the core paradigms as well as the design and evaluation methodologies to the learners. Results showed that the error rate for the FLM-2A predictions with Fitts’ Law enabled were 0.3% and 2.8% for the first and second apps respectively. A study investigated the accuracy of FLM-2A predictions by comparing them to participants’ interaction times for three custom-built Android apps. The tool aims to support design and evaluation of Android apps in an effective and efficient manner. This paper presents a novel tool, named FLM for Android Apps (FLM-2A), that supports automated FLM modeling of tasks performed in Android apps. Fingerstroke-Level Model (FLM) is such an extension for touch-sensitive interactions with direct finger movements. KLM was originally developed for desktop systems, but it has been extended for different interaction contexts. ![]() Keystroke-Level Model (KLM) is an established HCI model for predicting users’ time on task. The paper presents samples of the progress made between various versions of the models and concludes presenting the preliminary positive results of the students qualitative evaluation of this experiment. The use of these data offered them the insight to improve their models and to undergo design changes. The students created a working model of the system with limited functionality and improved this model using eye-tracking data from the peer evaluation of this model. The paper presents the setting of this experiment, the peer assessment method and the use of eye-tracking data collected and analysed to aid the students towards improving their design. This activity presented in this paper was the longest activity of the entire course and it was conducted in four consequent workshops. Then a system's description, vague enough to stimulate creativity, was randomly assigned to each group. The students were asked to form six groups comprising of three to four students each. The activity presented in this paper was the design and evaluation of an interactive system. For each workshop the students had to be prepared to participate, which was tested using brief quizzes before the start of specific workshops. ![]() Such material was mainly short lectures from the professor, in the form of videos uploaded in the course's YouTube channel and documents delivered using the university learning management system (LMS). All the rest of the educational material was offered to the students online before each workshop. Each workshop focused on a specific HCI activity, while before the workshops, a two-hour lecture was used to introduce the students in the flipped learning concept. The students that finished successfully this course participated in twelve short workshops, based on a flipped classroom model. course on Human-Computer Interaction (HCI). This paper presents experiences from a flipped classroom M.Sc.
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