Niederhauser, Mario

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Niederhauser
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Mario
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Niederhauser, Mario

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20211
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Enddatum: 2021 × Anfangsdatum: 2020 × Typ: 11 - Studentische Arbeit ×

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    Publikation
    Developing a New Method for Investigating Learning Behavior in Learning with Interactive Videos using Log Files
    (18.01.2021) Niederhauser, Mario; Zahn, Carmen; Ruf, Alessia; Institut für Kooperationsforschung – und entwicklung (IfK) Projekt: „Digital Video Tools to Support Conceputal Understanding and Creative Learning in Individuals and Groups" "gefördert vom Schweizer Nationalfond (SNF)
    Learning videos are a promising opportunity to enable remote learning and enjoy a worldwide increasing popularity. However, due to the remote setting it is difficult to examine students’ learning behavior. Previous research examined learners’ video interaction by focusing on fre-quencies of user interaction (i.e. clicks). However, we assume that investigating meaningful behavior sequences instead of click frequencies can lead to a better understanding of learning behavior. The main goal of this study was to develop a new method to gain deeper insights into learners’ behavior based on their digital footprints (i.e. log files) when they learned with an enhanced video-based environment. Yet, measuring a latent variable such as learning be-havior is particularly tricky and time consuming. Thus, we developed an application (Logible) based on our method to automatically analyze 92 log files from one of our prior studies. We contrasted four experimental conditions differing in learning task and learning setting. Results revealed that the learning task (i.e. using annotations or hyperlinks) had a significant influence on learning behavior. Yet, no significant influence caused by the learning setting (i.e. learning individually or collaboratively) was found. Furthermore, we investigated if and how learning strategies from successful and less successful learners differ. Results showed that successful learners more thoroughly planed where to to place annotations or hyperlinks. We conclude that applying Logible led to original findings and therefore we encourage fellow researchers in the field of CSCL to consider working with Logible whenever focusing on broader behavior instead of raw clickstream data.
    11 - Studentische Arbeit