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A Dialog About the Special Issues on Theory

A Dialog About the Special Issues on Theory AMY J. KO, University of Washington, USA STEVE DRAPER and JOSEPH MAGUIRE, University of Glasgow, UK JOHN PAJUNEN, University of Jyväskylä, Finland MATTI TEDRE, University of Eastern Finland, Finland JANE SINCLAIR, University of Warwick, UK CLAUDIA SZABO, University of Adelaide, Australia Several authors of articles in the special issue came together for an asynchronous discussion of the articles, surfacing several tensions and opportunities for future work. This summary of the discussion offers a glimpse into these insights. CCS Concepts: • Social and professional topics → Computing education; Additional Key Words and Phrases: Research methods, theoretical frameworks ACM Reference format: Amy J. Ko, Steve Draper, Joseph Maguire, John Pajunen, Matti Tedre, Jane Sinclair, and Claudia Szabo. 2023. A Dialog About the Special Issues on Theory. ACM Trans. Comput. Educ. 23, 1, Article 8 (January 2023), 5 pages. https://doi.org/10.1145/3554982 I first learned of the plans for this special issue when I started my role as Editor-in-Chief of ACM TOCE in December of 2021. Josh Tenenberg and Lauri Malmi had a compelling vision for bring- ing our community together to think deeply about our use of theory and think deeply about the theories we use. I was excited to see the articles the community had contributed, both as an editor and a member of the community. But I was also curious about how it might unfold, as just a few years prior in 2018, my then doctoral student Greg Nelson had published a somewhat controver- sial article at ACM ICER, trying to start a broader conversation about some of the unproductive ways our field has been using theory. Greg and I did not have the space to go deep; however, our contribution was a catalyst, and I hoped that Josh and Lauri’s skillful editing, along with the out- standing contributions of thought leaders across our community, would help all of us understand our broader relationship to theory. The issues do not disappoint. The ten articles, split across one issue that addresses specific theo- ries and families of theories and one issue that addresses the use of theory, are a broad, command- Authors’ addresses: A. J. Ko (Editor-in-Chief), University of Washington, Seattle, WA, USA; email: ajko@uw.edu; S. Draper and J. Maguire, University of Glasgow, Glasgow, UK; emails: {Steve.Draper, Joseph.Maguire}@glasgow.ac.uk; J. Pajunen, University of Jyväskylä, Jyväskylä, Finland; email: john.pajunen@jyu.fi; M. Tedre, University of Eastern Finland, Kuopio, Finland; email: matti.tedre@uef.fi; J. Sinclair, University of Warwick, Coventry, UK; email: j.e.sinclair@warwick.ac.uk; C. Szabo, University of Adelaide, Adelaide, Australia; email: claudia.szabo@adelaide.edu.au. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2023 Association for Computing Machinery. 1946-6226/2023/01-ART8 $15.00 https://doi.org/10.1145/3554982 ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. 8 8:2 A. J. Ko et al. ing, and provocative statement from our growing community. And so when Josh and Lauri asked if I would facilitate an edited dialog amongst the authors for inclusion in the special issue, I was glad to participate. The vision for the piece was simple: bring together a subset of authors who had written about the field’s use of theory, have them read articles of their choosing, and then discuss their reactions, ideas, and disagreements. Finally, I would summarize that discussion for the broader community to read. Josh and Lauri successfully recruited six of the authors to participate. Because of the timing of this activity (April, May, and June of 2022 during an exhausting global pandemic), I decided on a lightweight, highly asynchronous dialog. I created a shared document with links to the ten articles and a place for each of the six authors to write reactions to the articles and reactions to others reactions. We worked in two-week sprints, reading, reacting, and replying, and then I organized, synthesized, and summarized the discussion, curating a set of perspectives I thought might be of most interest to our community. The discussion is too extensive to publish here, and 1, 2 so below I summarize themes from the discussion and bring my editorial perspective to them. One of the most salient aspects of the discussion was just how invaluable the participants found the articles that summarized existing theories to be. Multiple authors noted how many of the articles ought to be required reading for new doctoral students entering our field. Duran et al.’s Cognitive Load Theory in Computing Education Research: A Review, Loksa et al.’s Metacognition and Self-Regulation in Programming Education: Theories and Exemplars of Use, Michaelis and Weintrop’s Interest Development Theory in Computing Education: A Framework and Toolkit for Researchers and Designers, and Robins’ Dual Process Theories: Computing Cognition in Context particularly captured the authors’ attention. I particularly liked Steve Draper’s reaction to Robins’ article: For a new PhD student in CER wondering what topic to pick, they could do a lot worse than jab a pin into this article at random and construct a topic out of where the pin fell. Littleornoneofithas been appliedinCER,soitwould beanovel topic, andthe clear writing and well-selected references would be great pointers for getting started on the theory. —Steve Draper But the summaries of theories also catalyzed new ideas. Jane Sinclair, for example, reacted to the Loksa et al. article by wondering about the many things we are not theorizing about: On the face of it, the nature of learning to program seems ripe for subject-specific de- velopments of these theories. We very often focus on programming as it is the most obvious, central topic and seems to have particularities that make it different from other learning. But we often seem to focus solely on programming. What other ar- eas of CER do, or could there be differences that lead to subject-specific adaptations? —Jane Sinclair While the authors viewed the articles summarizing theories as invaluable, most of the authors chose to read the other set of articles, discussing and reflecting on our use of theory. One article in particular, Tedre and Pajunen’s Grand Theories or Design Guidelines? Perspectives on the Role of Theory in Computing Education Research, was particularly provocative. Claudia, for example, noted: I think the essay identifies a critical issue within the theoretical work in CER and definitely reflects our frustrations when trying to both come up with a definition of learning theory but also to determine whether works fall into a theory or a model All of the participants are listed as co-authors in recognition of their participation and review and editing of this summary. Throughout, CER refers to “Computing Education Research.” ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. A Dialog About the Special Issues on Theory 8:3 category...I do not think, though, that the emotional/conceptual/philosophical bag- gage is the reason why we struggle as a discipline but rather because there is no broad knowledge of what theories/models are out there, so when people start their work, they either employ a theory they are familiar with or try to fit in a theory/model after the fact, e.g., because a specific conference might require a theoretical background. In the articles that Judy and I read, we found a lot of theories/models that were simply mentioned in passing or as “our work is mostly related to...” —Claudia Szabo Joseph interpreted the arguments of the article similarly, drawing a compelling analogy in his summary of the article: Using theory, like a bogeyman in this sense, is problematic. For one, theory may take on different meanings, potentially as a barometer of competency. A good child or re- searcher cements contributions or relates them to theory. A bad child or researcher makes no reference to theory. The consequence is that some researchers may make passing or incorrect references to theory to navigate review processes, but their con- tributions are not actually informed or cemented in theory. Another potential con- sequence is that researchers rejected for lack of theory (and feel they are being la- belled incompetent), rally against theory, dismissing its relevance, despite its value. —Joseph Maguire Steve had a different reaction, pondering how much space there is in a discipline for non- theoretical contributions, pointing to a significant non-theoretical contribution in Chemistry: Just the action of considering forms of knowledge that are valuable but not “theory” (i.e., models, guidelines, patterns...) is a major help in building a more balanced and considered view of what knowledge in a disciplinary area actually consists of. If an incautious editor were to require articles to relate their work to “theory,” it is likely to be interpreted as excluding guidelines (and models and patterns). Yet even in the heartland of past science, some of the major triumphs are not exact predictions or rules. The periodic table shows a pattern over a set of elements—and conventionally most say there are 92 elements. Yet, in fact, the rules behind it say there are infinitely many elements, it is just that most have no stable form; and contrariwise, there are more than 4 of the 92 with no stable form and yet are listed [Technetium (43), Promethium (61), Bismuth (83), Uranium (92),...]. So the rules it encodes are not exact, but right from its publication and still today it supported useful (but not fully reliable) predictions, so much so that it is still taught to schoolchildren. A periodic table of learning designs in CER would be a huge advance. —Steve Draper While the Tedre and Pajunen article captured much of the authors’ attention, other articles com- plemented this discussion of why and how we use theory, and what else we might build. Matti and John engaged Joseph and Steve, for example, on their article, The Different Types of Contributions to Knowledge (in CER): All Needed, But Not All Recognised. Matti remarked: There is a need to acknowledge the usefulness of and need for research contributions other than just theory-driven. A much broader variety of contributions have always played an important role in sciences, and there is no logical reason at this point to think that CER would be so radically different that it could not benefit from similar contributions. What is more, I wish that this essay succeeds in at least slightly shifting the field’s soul-seeking discussions from “types of article” (methodology, theory) to- ward “types of contributions to knowledge.” While meta-reviews have been extremely ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. 8:4 A. J. Ko et al. important for CER’s disciplinary self-understanding (thanks, Simon!) there is a need to broaden them, too. —Matti Tedre And John built on this, wondering what if we often operate under false assumptions about the nature of our scholarly work: How science is done, or what is the recipe for scientific knowledge? Methodology is often cashed out in practice as a process with a number of steps, say 7 or so, starting with a definition of a problem and choosing methods to answer the question and lead- ing into publishing results. Like following a recipe to bake a cake. As helpful as this way of describing a research process can be, it at the same time can cause frustration as everything can end up going in a different way, and in addition, research activities are not just theory testing (in a simplified or vulgar Popperian sense). This article, I think, makes it very visible that scientific knowledge production is not mere standardised factory producing and testing epistemic goods called theories. —John Pajunen Two of the articles were not commented on by the participants (although some did read them). One was one of my personal favorites, Vrieler and Salminen-Karlsson’s A Sociocultural Perspec- tive on Computer Science Capital and Its Pedagogical Implications in Computer Science Education.It was perhaps the greatest reach outside the conventions of our community, invoking Bourdieu’s sociological theory of capital and Archer et al.’s work on science capital to explain wide-ranging phenomena in CS teaching and learning, including identity, interest, norms, beliefs, and more. Our community most often engages with the mind, responding to the calls of many of the articles to look more broadly, it might mean engaging with our collective social systems and structures. Many of the participants expressed the benefits of reading others’ contributions and then dis- cussing them, with many generating new ideas in their replies to each other. This was particularly evident in some of the discussions in which authors of an article replied to reactions to their ar- ticle by other authors. For example, John made several comments about the The different types of contributions to knowledge (in CER), raising questions about the function of theory in our field and suggesting a direction for future work: Apart from loosening up from too strict a notion of theory-entities, a good question is to think about functions of theories, and this is a major point in this article. The writers take this up, and their take is informative also in terms of the categories. A direction I would take the analysis is philosophy: epistemology and ontology would shed light on the categories, especially as methodologies are about how to gain knowledge about the world, and epistemologists have come up with various facets of knowledge issues, and metaphysicians have investigated the fundamental ontological concepts. Steve replied, appreciating these nuances, and noting how complementary their articles were to each other in making space for more nuance about theory and progress: John’s article with Matti is in my opinion a very good companion article to ours for several reasons. Most basically, the main message of ours is that there are many types of contribution to scientific knowledge, and theory is only one. Thus, to maintain that emphasis our article could only comment a rather small amount on the nature of theory. John has commented on our article that there are important points to make about different kinds of theory: frameworks, guidelines, and so on, and I agree with him. His and Matti’s article in this issue addresses this at length and is, thus, in my opinion, a very good companion article to ours, which I would recommend to readers forthatreason. ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. A Dialog About the Special Issues on Theory 8:5 This discussion continued, as the authors of these two complementary works charted possible next steps for theory in our field. This dialog was not everything it could have been; many authors were unable to participate, and there were the usual challenges of engaging busy researchers through an occasional email nudge. But for those who could participate, thank you: I learned an immense amount from your dialogue and hope my summary captures some small glimpse of its brilliance. I would encourage everyone in our community to make time to read these important contributions and encourage their students and collaborators too read them as well. I suspect you will find countless opportunities to test some of the theories detailed, to apply them to teaching and learning, to refine how we engage and peer review the use of theory, and how we ultimately make progress on advancing computing education. And we hope you will consider ACM Transactions on Computing Education for all of these contributions. Received 29 July 2022; revised 29 July 2022; accepted 2 August 2022 ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Computing Education (TOCE) Association for Computing Machinery

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Association for Computing Machinery
Copyright
Copyright © 2023 Association for Computing Machinery.
ISSN
1946-6226
eISSN
1946-6226
DOI
10.1145/3554982
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Abstract

AMY J. KO, University of Washington, USA STEVE DRAPER and JOSEPH MAGUIRE, University of Glasgow, UK JOHN PAJUNEN, University of Jyväskylä, Finland MATTI TEDRE, University of Eastern Finland, Finland JANE SINCLAIR, University of Warwick, UK CLAUDIA SZABO, University of Adelaide, Australia Several authors of articles in the special issue came together for an asynchronous discussion of the articles, surfacing several tensions and opportunities for future work. This summary of the discussion offers a glimpse into these insights. CCS Concepts: • Social and professional topics → Computing education; Additional Key Words and Phrases: Research methods, theoretical frameworks ACM Reference format: Amy J. Ko, Steve Draper, Joseph Maguire, John Pajunen, Matti Tedre, Jane Sinclair, and Claudia Szabo. 2023. A Dialog About the Special Issues on Theory. ACM Trans. Comput. Educ. 23, 1, Article 8 (January 2023), 5 pages. https://doi.org/10.1145/3554982 I first learned of the plans for this special issue when I started my role as Editor-in-Chief of ACM TOCE in December of 2021. Josh Tenenberg and Lauri Malmi had a compelling vision for bring- ing our community together to think deeply about our use of theory and think deeply about the theories we use. I was excited to see the articles the community had contributed, both as an editor and a member of the community. But I was also curious about how it might unfold, as just a few years prior in 2018, my then doctoral student Greg Nelson had published a somewhat controver- sial article at ACM ICER, trying to start a broader conversation about some of the unproductive ways our field has been using theory. Greg and I did not have the space to go deep; however, our contribution was a catalyst, and I hoped that Josh and Lauri’s skillful editing, along with the out- standing contributions of thought leaders across our community, would help all of us understand our broader relationship to theory. The issues do not disappoint. The ten articles, split across one issue that addresses specific theo- ries and families of theories and one issue that addresses the use of theory, are a broad, command- Authors’ addresses: A. J. Ko (Editor-in-Chief), University of Washington, Seattle, WA, USA; email: ajko@uw.edu; S. Draper and J. Maguire, University of Glasgow, Glasgow, UK; emails: {Steve.Draper, Joseph.Maguire}@glasgow.ac.uk; J. Pajunen, University of Jyväskylä, Jyväskylä, Finland; email: john.pajunen@jyu.fi; M. Tedre, University of Eastern Finland, Kuopio, Finland; email: matti.tedre@uef.fi; J. Sinclair, University of Warwick, Coventry, UK; email: j.e.sinclair@warwick.ac.uk; C. Szabo, University of Adelaide, Adelaide, Australia; email: claudia.szabo@adelaide.edu.au. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. © 2023 Association for Computing Machinery. 1946-6226/2023/01-ART8 $15.00 https://doi.org/10.1145/3554982 ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. 8 8:2 A. J. Ko et al. ing, and provocative statement from our growing community. And so when Josh and Lauri asked if I would facilitate an edited dialog amongst the authors for inclusion in the special issue, I was glad to participate. The vision for the piece was simple: bring together a subset of authors who had written about the field’s use of theory, have them read articles of their choosing, and then discuss their reactions, ideas, and disagreements. Finally, I would summarize that discussion for the broader community to read. Josh and Lauri successfully recruited six of the authors to participate. Because of the timing of this activity (April, May, and June of 2022 during an exhausting global pandemic), I decided on a lightweight, highly asynchronous dialog. I created a shared document with links to the ten articles and a place for each of the six authors to write reactions to the articles and reactions to others reactions. We worked in two-week sprints, reading, reacting, and replying, and then I organized, synthesized, and summarized the discussion, curating a set of perspectives I thought might be of most interest to our community. The discussion is too extensive to publish here, and 1, 2 so below I summarize themes from the discussion and bring my editorial perspective to them. One of the most salient aspects of the discussion was just how invaluable the participants found the articles that summarized existing theories to be. Multiple authors noted how many of the articles ought to be required reading for new doctoral students entering our field. Duran et al.’s Cognitive Load Theory in Computing Education Research: A Review, Loksa et al.’s Metacognition and Self-Regulation in Programming Education: Theories and Exemplars of Use, Michaelis and Weintrop’s Interest Development Theory in Computing Education: A Framework and Toolkit for Researchers and Designers, and Robins’ Dual Process Theories: Computing Cognition in Context particularly captured the authors’ attention. I particularly liked Steve Draper’s reaction to Robins’ article: For a new PhD student in CER wondering what topic to pick, they could do a lot worse than jab a pin into this article at random and construct a topic out of where the pin fell. Littleornoneofithas been appliedinCER,soitwould beanovel topic, andthe clear writing and well-selected references would be great pointers for getting started on the theory. —Steve Draper But the summaries of theories also catalyzed new ideas. Jane Sinclair, for example, reacted to the Loksa et al. article by wondering about the many things we are not theorizing about: On the face of it, the nature of learning to program seems ripe for subject-specific de- velopments of these theories. We very often focus on programming as it is the most obvious, central topic and seems to have particularities that make it different from other learning. But we often seem to focus solely on programming. What other ar- eas of CER do, or could there be differences that lead to subject-specific adaptations? —Jane Sinclair While the authors viewed the articles summarizing theories as invaluable, most of the authors chose to read the other set of articles, discussing and reflecting on our use of theory. One article in particular, Tedre and Pajunen’s Grand Theories or Design Guidelines? Perspectives on the Role of Theory in Computing Education Research, was particularly provocative. Claudia, for example, noted: I think the essay identifies a critical issue within the theoretical work in CER and definitely reflects our frustrations when trying to both come up with a definition of learning theory but also to determine whether works fall into a theory or a model All of the participants are listed as co-authors in recognition of their participation and review and editing of this summary. Throughout, CER refers to “Computing Education Research.” ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. A Dialog About the Special Issues on Theory 8:3 category...I do not think, though, that the emotional/conceptual/philosophical bag- gage is the reason why we struggle as a discipline but rather because there is no broad knowledge of what theories/models are out there, so when people start their work, they either employ a theory they are familiar with or try to fit in a theory/model after the fact, e.g., because a specific conference might require a theoretical background. In the articles that Judy and I read, we found a lot of theories/models that were simply mentioned in passing or as “our work is mostly related to...” —Claudia Szabo Joseph interpreted the arguments of the article similarly, drawing a compelling analogy in his summary of the article: Using theory, like a bogeyman in this sense, is problematic. For one, theory may take on different meanings, potentially as a barometer of competency. A good child or re- searcher cements contributions or relates them to theory. A bad child or researcher makes no reference to theory. The consequence is that some researchers may make passing or incorrect references to theory to navigate review processes, but their con- tributions are not actually informed or cemented in theory. Another potential con- sequence is that researchers rejected for lack of theory (and feel they are being la- belled incompetent), rally against theory, dismissing its relevance, despite its value. —Joseph Maguire Steve had a different reaction, pondering how much space there is in a discipline for non- theoretical contributions, pointing to a significant non-theoretical contribution in Chemistry: Just the action of considering forms of knowledge that are valuable but not “theory” (i.e., models, guidelines, patterns...) is a major help in building a more balanced and considered view of what knowledge in a disciplinary area actually consists of. If an incautious editor were to require articles to relate their work to “theory,” it is likely to be interpreted as excluding guidelines (and models and patterns). Yet even in the heartland of past science, some of the major triumphs are not exact predictions or rules. The periodic table shows a pattern over a set of elements—and conventionally most say there are 92 elements. Yet, in fact, the rules behind it say there are infinitely many elements, it is just that most have no stable form; and contrariwise, there are more than 4 of the 92 with no stable form and yet are listed [Technetium (43), Promethium (61), Bismuth (83), Uranium (92),...]. So the rules it encodes are not exact, but right from its publication and still today it supported useful (but not fully reliable) predictions, so much so that it is still taught to schoolchildren. A periodic table of learning designs in CER would be a huge advance. —Steve Draper While the Tedre and Pajunen article captured much of the authors’ attention, other articles com- plemented this discussion of why and how we use theory, and what else we might build. Matti and John engaged Joseph and Steve, for example, on their article, The Different Types of Contributions to Knowledge (in CER): All Needed, But Not All Recognised. Matti remarked: There is a need to acknowledge the usefulness of and need for research contributions other than just theory-driven. A much broader variety of contributions have always played an important role in sciences, and there is no logical reason at this point to think that CER would be so radically different that it could not benefit from similar contributions. What is more, I wish that this essay succeeds in at least slightly shifting the field’s soul-seeking discussions from “types of article” (methodology, theory) to- ward “types of contributions to knowledge.” While meta-reviews have been extremely ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. 8:4 A. J. Ko et al. important for CER’s disciplinary self-understanding (thanks, Simon!) there is a need to broaden them, too. —Matti Tedre And John built on this, wondering what if we often operate under false assumptions about the nature of our scholarly work: How science is done, or what is the recipe for scientific knowledge? Methodology is often cashed out in practice as a process with a number of steps, say 7 or so, starting with a definition of a problem and choosing methods to answer the question and lead- ing into publishing results. Like following a recipe to bake a cake. As helpful as this way of describing a research process can be, it at the same time can cause frustration as everything can end up going in a different way, and in addition, research activities are not just theory testing (in a simplified or vulgar Popperian sense). This article, I think, makes it very visible that scientific knowledge production is not mere standardised factory producing and testing epistemic goods called theories. —John Pajunen Two of the articles were not commented on by the participants (although some did read them). One was one of my personal favorites, Vrieler and Salminen-Karlsson’s A Sociocultural Perspec- tive on Computer Science Capital and Its Pedagogical Implications in Computer Science Education.It was perhaps the greatest reach outside the conventions of our community, invoking Bourdieu’s sociological theory of capital and Archer et al.’s work on science capital to explain wide-ranging phenomena in CS teaching and learning, including identity, interest, norms, beliefs, and more. Our community most often engages with the mind, responding to the calls of many of the articles to look more broadly, it might mean engaging with our collective social systems and structures. Many of the participants expressed the benefits of reading others’ contributions and then dis- cussing them, with many generating new ideas in their replies to each other. This was particularly evident in some of the discussions in which authors of an article replied to reactions to their ar- ticle by other authors. For example, John made several comments about the The different types of contributions to knowledge (in CER), raising questions about the function of theory in our field and suggesting a direction for future work: Apart from loosening up from too strict a notion of theory-entities, a good question is to think about functions of theories, and this is a major point in this article. The writers take this up, and their take is informative also in terms of the categories. A direction I would take the analysis is philosophy: epistemology and ontology would shed light on the categories, especially as methodologies are about how to gain knowledge about the world, and epistemologists have come up with various facets of knowledge issues, and metaphysicians have investigated the fundamental ontological concepts. Steve replied, appreciating these nuances, and noting how complementary their articles were to each other in making space for more nuance about theory and progress: John’s article with Matti is in my opinion a very good companion article to ours for several reasons. Most basically, the main message of ours is that there are many types of contribution to scientific knowledge, and theory is only one. Thus, to maintain that emphasis our article could only comment a rather small amount on the nature of theory. John has commented on our article that there are important points to make about different kinds of theory: frameworks, guidelines, and so on, and I agree with him. His and Matti’s article in this issue addresses this at length and is, thus, in my opinion, a very good companion article to ours, which I would recommend to readers forthatreason. ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023. A Dialog About the Special Issues on Theory 8:5 This discussion continued, as the authors of these two complementary works charted possible next steps for theory in our field. This dialog was not everything it could have been; many authors were unable to participate, and there were the usual challenges of engaging busy researchers through an occasional email nudge. But for those who could participate, thank you: I learned an immense amount from your dialogue and hope my summary captures some small glimpse of its brilliance. I would encourage everyone in our community to make time to read these important contributions and encourage their students and collaborators too read them as well. I suspect you will find countless opportunities to test some of the theories detailed, to apply them to teaching and learning, to refine how we engage and peer review the use of theory, and how we ultimately make progress on advancing computing education. And we hope you will consider ACM Transactions on Computing Education for all of these contributions. Received 29 July 2022; revised 29 July 2022; accepted 2 August 2022 ACM Transactions on Computing Education, Vol. 23, No. 1, Article 8. Publication date: January 2023.

Journal

ACM Transactions on Computing Education (TOCE)Association for Computing Machinery

Published: Jan 24, 2023

Keywords: Research methods

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