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DOI: 10.4230/LIPIcs.SNAPL.2017.13

Teaching Programming Languages by Experimental and Adversarial Thinking

Authors: Justin Pombrio, Shriram Krishnamurthi, and Kathi Fisler

Published in: LIPIcs, Volume 71, 2nd Summit on Advances in Programming Languages (SNAPL 2017)

Abstract

We present a new approach to teaching programming language courses. Its essence is to view programming language learning as a natural science activity, where students probe languages experimentally to understand both the normal and extreme behaviors of their features. This has natural parallels to the "security mindset" of computer security, with languages taking the place of servers and other systems. The approach is modular (with minimal dependencies), incremental (it can be introduced slowly into existing classes), interoperable (it does not need to push out other, existing methods), and complementary (since it introduces a new mode of thinking).

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Justin Pombrio, Shriram Krishnamurthi, and Kathi Fisler. Teaching Programming Languages by Experimental and Adversarial Thinking. In 2nd Summit on Advances in Programming Languages (SNAPL 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 71, pp. 13:1-13:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{pombrio_et_al:LIPIcs.SNAPL.2017.13,
  author =	{Pombrio, Justin and Krishnamurthi, Shriram and Fisler, Kathi},
  title =	{{Teaching Programming Languages by Experimental and Adversarial Thinking}},
  booktitle =	{2nd Summit on Advances in Programming Languages (SNAPL 2017)},
  pages =	{13:1--13:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-032-3},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{71},
  editor =	{Lerner, Benjamin S. and Bod{\'\i}k, Rastislav and Krishnamurthi, Shriram},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SNAPL.2017.13},
  URN =		{urn:nbn:de:0030-drops-71178},
  doi =		{10.4230/LIPIcs.SNAPL.2017.13},
  annote =	{Keywords: mystery languages, interpreters, paradigms, education}
}

Document

DOI: 10.4230/DagRep.6.2.78

Assessing Learning In Introductory Computer Science (Dagstuhl Seminar 16072)

Authors: Michael E. Caspersen, Kathi Fisler, and Jan Vahrenhold

Published in: Dagstuhl Reports, Volume 6, Issue 2 (2016)

Abstract

This seminar discussed educational outcomes for first-year (university-level) computer science. We explored which outcomes were widely shared across both countries and individual universities, best practices for assessing outcomes, and research projects that would significantly advance assessment of learning in computer science. We considered both technical and professional outcomes (some narrow and some broad) as well as how to create assessments that focused on individual learners. Several concrete research projects took shape during the seminar and are being pursued by some participants.

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Michael E. Caspersen, Kathi Fisler, and Jan Vahrenhold. Assessing Learning In Introductory Computer Science (Dagstuhl Seminar 16072). In Dagstuhl Reports, Volume 6, Issue 2, pp. 78-96, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@Article{caspersen_et_al:DagRep.6.2.78,
  author =	{Caspersen, Michael E. and Fisler, Kathi and Vahrenhold, Jan},
  title =	{{Assessing Learning In Introductory Computer Science (Dagstuhl Seminar 16072)}},
  pages =	{78--96},
  journal =	{Dagstuhl Reports},
  ISSN =	{2192-5283},
  year =	{2016},
  volume =	{6},
  number =	{2},
  editor =	{Caspersen, Michael E. and Fisler, Kathi and Vahrenhold, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagRep.6.2.78},
  URN =		{urn:nbn:de:0030-drops-58899},
  doi =		{10.4230/DagRep.6.2.78},
  annote =	{Keywords: Assessment, Learning Objectives}
}

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Documents authored by Fisler, Kathi

Teaching Programming Languages by Experimental and Adversarial Thinking

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Assessing Learning In Introductory Computer Science (Dagstuhl Seminar 16072)

Abstract

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