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    Chapter 14: Technologies and Student Feedback Collection and Analysis

    Technology-enabled feedback encompasses many significant features including AI. It also allows students greater flexibility in providing feedback, and the university/institute enables them to make data-driven decisions as the collected data are free from bias and data analyses are accurate. There are different technology-centric feedback collections such as Open edX Insight, speech-to-text, Kahoot, Dialogflow, and so on. These technology-centric feedback collections mean collecting more realistic data from the students. Both qualitative and quantitative data could be analyzed by applying technology-centric data analyses tools. AMOS, LABLEAU, SAS, SPSS, Stata, Statista, XLSTAT, and ROOT are a few of the quantitative data analyses software, and Atlas, Airtable, Coda, Condens, MaxQDA, Notion, and NVivo are a few of the qualitative data analyses software. To make the students’ feedback and survey more successful we recommend sharing survey methods/survey questions with other educational institutions, conducting broader surveys, broad topics to ask questions on, technology-based analysis of qualitative feedback comments, and including skills development-focused questions.

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    INDEXING ADAPTABILITY ANALYSIS OF eLEARNING

    This paper presents the design of an eLearning Index (eLI) to determine the adaptability of a corporation or education institution for eLearning. Firstly, it describes the framework of eLearning. Secondly, it describes the methodology and the evaluation of eLearning Index. Thirdly, it reports the research results of two surveys. Finally, it concludes its findings on how to assess an organization's adaptability to eLearning. The principal aim of this paper is to design an eLI which is used to determine the adaptability of a corporation or education institution to eLearning before full implementation of an eLearning strategy. In the determination of eLI, staff of a corporation or education institution are required to answer twenty key questions. The average score of the eLI of the staff is used to determine the adaptability to eLearning. The higher the average score of the eLI is, the better the adaptability of the corporation or education institution to eLearning is.