Abstract:Educational software is somewhat unique in that the goal of the software is not to facilitate use of the software itself, but to produce an impact on the user - learning - that will affect the user's behavior outside of the software. Although there are many areas where educational software designers can learn from practices in productivity and game design, there are reasons to be cautious in applying such principles to educational software. This chapter considers several design elements in educational software… Show more
“…It further encouraged students to self-learn, exchange ideas, and integrate into learning through digital platform environments. Ritter et al (2018) confirmed that educational programs offered by universities did not help students to engage and integrate them (Ritter et al, 2018). The reason for this was that the educational software template was similar to the educational book template in terms of showing chapters, lessons, and activities to students.…”
The current study sought to develop engagement skills in learning and digital trust among university students by designing an interactive e-learning environment based on integrating the edX digital platform with some artificial intelligence applications. It was achieved by a random sample of undergraduate students at the College of Education, King Khalid University, was selected and divided into two groups: The first empirical group numbered (28) students and used the edX platform with some AI applications, and the other empirical group numbered (29) students who used Blackboard platform. A scale of engagement in learning was prepared, and a scale of digital trust and a t-test were used to analyze the study’s findings. The study found a statistical significance between integrating the edX digital platform with some AI applications and the Blackboard platform in developing engagement skills in learning in favor of the edX digital platform. The calculated T-value for both groups was 7.923, statistically significant at p<0.05. The T-value for integrating the edX digital platform with some AI and the Blackboard platform applications in developing digital trust skills in both groups was 1.368, which was insignificant at p<0.05.
“…It further encouraged students to self-learn, exchange ideas, and integrate into learning through digital platform environments. Ritter et al (2018) confirmed that educational programs offered by universities did not help students to engage and integrate them (Ritter et al, 2018). The reason for this was that the educational software template was similar to the educational book template in terms of showing chapters, lessons, and activities to students.…”
The current study sought to develop engagement skills in learning and digital trust among university students by designing an interactive e-learning environment based on integrating the edX digital platform with some artificial intelligence applications. It was achieved by a random sample of undergraduate students at the College of Education, King Khalid University, was selected and divided into two groups: The first empirical group numbered (28) students and used the edX platform with some AI applications, and the other empirical group numbered (29) students who used Blackboard platform. A scale of engagement in learning was prepared, and a scale of digital trust and a t-test were used to analyze the study’s findings. The study found a statistical significance between integrating the edX digital platform with some AI applications and the Blackboard platform in developing engagement skills in learning in favor of the edX digital platform. The calculated T-value for both groups was 7.923, statistically significant at p<0.05. The T-value for integrating the edX digital platform with some AI and the Blackboard platform applications in developing digital trust skills in both groups was 1.368, which was insignificant at p<0.05.
The aim of this study is to analyze the effectiveness of screencast training videos for users from different professional backgrounds on the basis of the quality and quantity of virtual 3D implant planning as evaluated using assessment software. Methods: Participants in the study were dental students (n = 21), dental technicians (n = 16), or practicing dentists (n = 16) with no knowledge of the implant planning software CoDiagnostiX or any experience in virtual implant planning. They were randomly divided into 2 groups: The participants of the control group were presented training videos on CBCT (cone beam computed tomography) and implant planning, additional to the traditional software manual. The participants of the experimental group received, additionally, a training video on the planning software, produced in the form of a screencast. Then 3 implant planning procedures were performed by all participants. The quality of implant planning was assessed using the Treatment Evaluation Tool software, and time for planning was measured. Results: Paired sample tests showed significantly shorter planning times for the experimental groups consisting of dentists and students (P < 0.001). A comparison of the results of the individual groups reveals that students and dental technicians who had not received prior screencast training were significantly less precise in their planning (P < 0.001). Conclusion: This study suggests a promising outcome for the future use of screencasts in the acquisition of software skills for dental software. There is a need for tools for objective self-assessment of effectiveness in software training.
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