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The Learning Ideas Conference

TLIC 2021: Innovations in Learning and Technology for the Workplace and Higher Education pp 396–408Cite as

AI-Based Multilingual Interactive Exam Preparation

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 349))

Abstract

Our previous analysis on 26 languages which represent over 2.9 billion speakers and 8 language families demonstrated that cross-lingual automatic short answer grading allows students to write answers in exams in their native language and graders to rely on the scores of the system [1]. With lower deviations than 14% (0.72 points out of 5 points) on the corpus of the short answer grading data set of the University of North Texas [2], our natural language processing models show better performances compared to the human grader variability (0.75 points, 15%). In this paper we describe our latest analysis of the integration and application of a multilingual model in interactive training programs to optimally prepare students for exams. We present a multilingual interactive conversational artificial intelligence tutoring system for exam preparation. Our approach leverages and combines learning analytics, crowdsourcing and gamification to automatically allow us to evaluate and adapt the system as well as to motivate students and increase their learning experience. In order to have an optimal learning effect and enhance the user experience, we also tackle the challenge of explainability with the help of keyword extraction and highlighting techniques. Our system is based on Telegram since it can be easily integrated into massive open online courses and other online study systems and has already more than 400 million users worldwide [3].

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Author information

Authors and Affiliations

  1. IU International University of Applied Sciences, Bad Honnef, Germany

    Tim Schlippe & Jörg Sawatzki

Authors
  1. Tim Schlippe
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  2. Jörg Sawatzki
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Corresponding author

Correspondence to Tim Schlippe .

Editor information

Editors and Affiliations

  1. Kaleidoscope Learning, International E-Learning Association, New York, NY, USA

    David Guralnick

  2. Carinthia University of Applied Sciences, St. Magdalen, Austria

    Michael E. Auer

  3. Università degli Studi di Modena e Reggio Emilia, Rome, Italy

    Antonella Poce

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Schlippe, T., Sawatzki, J. (2022). AI-Based Multilingual Interactive Exam Preparation. In: Guralnick, D., Auer, M.E., Poce, A. (eds) Innovations in Learning and Technology for the Workplace and Higher Education. TLIC 2021. Lecture Notes in Networks and Systems, vol 349. Springer, Cham. https://doi.org/10.1007/978-3-030-90677-1_38

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