DM-talk: Adish Singla (Max Planck Institute for Software Systems, Saabrücken)

You are cordially invited to the Data Mining and Machine Learning-Talk with Adish Singla (Max Planck Institute for Software Systems, Saabrücken). Title of the talk: "AI-Driven Educational Technology for Introductory Programming".

When?

Monday, 20.2.2023, 10:00

Where?

Fakultät für Informatik, Währinger Straße 29, 1090 Wien, HS3

Abstract

Computational thinking and basic programming skills are essential for everyone in the 21st century, both for students and adults, to thrive in the digital society. Consequently, there is an increasing emphasis on introducing computing and programming education at an early age, starting at elementary-level grades. However, given the conceptual and open-ended nature of programming tasks, novice learners often struggle when solving programming tasks by themselves. Given the scarcity of human tutoring resources to provide individualized assistance, AI-driven educational technology has the potential to provide scalable and automated assistance to struggling learners. In this talk, I will present our work on AI-driven programming education empowered by automated techniques for synthesizing new practice tasks, generating personalized feedback, and modeling learners' knowledge. I will describe unique challenges and opportunities in the programming domain, which can also drive the next scientific breakthroughs in AI-driven education for other subject domains. I will conclude with a discussion of crucial ingredients to succeed in making programming education easier and accessible for all.

Biography

Adish Singla is a faculty member at the Max Planck Institute for Software Systems (MPI-SWS), Germany, where he has been leading the Machine Teaching Group since 2017. He conducts research in the area of Machine Teaching, with a particular focus on open-ended learning and problem-solving domains. In recent years, his research has centered around developing AI-driven techniques to support learners and teachers in introductory programming environments. He has received several awards for his research, including an AAAI Outstanding Paper Honorable Mention Award (2022) and an ERC Starting Grant (2021). He also has extensive experience working in the industry and is a recipient of several industry awards, including a research grant from Microsoft Research Ph.D. Scholarship Programme (2018), Facebook Graduate Fellowship (2015), Microsoft Tech Transfer Award (2011), and Microsoft Gold Star Award (2010).

Organiser:

Data Mining and Machine Learning (DM)

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