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  • 1. Adams, Robin
    et al.
    Fincher, Sally
    Pears, Arnold
    Börstler, Jürgen
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Dalenius, Peter
    Eken, Gunilla
    Heyer, Tim
    Jacobsson, Andreas
    Lindberg, Vanja
    Molin, Bengt
    Moström, Jan-Erik
    Wiggberg, Mattias
    What is the word for 'Engineering' in Swedish: Swedish students conceptions of their discipline2007Report (Other academic)
    Abstract [en]

    Engineering education in Sweden – as in the rest of the world – is experiencing a decline in student interest. There are concerns about the ways in which students think about engineering education, why they join an academic programme in engineering, and why they persist in their studies. In this context the aims of the Nationellt ämnesdidaktiskt Centrum för Teknikutbildning i Studenternas Sammanhang project (CeTUSS) is to investigate the student experience and to identify and support a continuing network of interested researchers, as well as in building capacity for disciplinary pedagogic investigation.

    The Stepping Stones project brings together these interests in a multi-researcher, multi-institutional study that investigates how tudents and academic staff perceive engineering in Sweden and in Swedish education. The first results of that project are reported here. As this study is situated uniquely in Swedish education, it allows for exploration of “a Swedish perspective” on conceptions of engineering. The Stepping Stones project was based on a model of research capacity-building previously instantiated in the USA and Australia (Fincher & Tenenberg, 2006).

  • 2.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    A methodology for exploring students’ experiences and interaction with large-scale software through role-play and phenomenography2008In: ICER '08: proceedings of the fourth international workshop on Computing education research, New York: ACM , 2008, p. 27-38Conference paper (Refereed)
    Abstract [en]

    Traditional interview methods within qualitative research often capture the purely academic perspective on phenomena. To address this problem, an innovative research method, combining role-playing with phenomenography is proposed. The approach suggested in this paper aims to stimulate participants to widen their perspectives by encouraging them to a deeper engagement with a specific activity, thereby enabling them to reflect actively on their actions and on concepts involved in a specific situated context. In the outlined strategy, the role-playing involved realistic work with large-scale software. This was immediately followed by a debriefing using phenomenographic research interviews when the participants still had the experience fresh in mind. The phenomenographic analysis of the interview transcripts confirmed that the method was successful. The subjects frequently expressed their understanding of theoretical concepts in relation to their experiences from working with the software. The more advanced ways to experience the phenomena was often expressed – and sometimes inspired – by the software’s way to take advantage of the concepts. The specific use of the described method resulted in empirical insights into how students experience object-oriented concepts in software engineering, such as the Java Interface.

  • 3.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    A Student Perspective on Software Development and Maintenance2010Report (Other academic)
    Abstract [en]

    How do Computer Science students view Software Development and Software Maintenance? To answer this question, a Phenomenographic perspective was chosen, and 20 Swedish students at four universities were interviewed.

    The interviews were analyzed to find in which different ways the informants, on collective level, see the phenomena of interest. The resulting outcome spaces show that software development is described in a number of qualitatively different ways reaching from problem solving, design and deliver, design for the future and then a more comprehensive view that includes users, customers, budget and other aspects. Software maintenance is described as correcting bugs, making additions, adapting to new requirements from the surroundings, and something that is a natural part of the job.

    Finally, conclusions from the results and additional observations are discussed in terms of their implications for teaching, and some suggestions for practical use are given.

  • 4.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Automated Analysis of Dynamic Web Services2002Report (Other academic)
    Abstract [en]

    For a web application test-engineer, it would be convenient to have a map, in form of a graph, describing the functional topology of the application. In that way, it would be possible to analyse the possible paths which can be navigated to discover redundancies and circularities for example. A web spider tool can automate the construction of such a graph. The spider can request a document from the application, find all references to other documents in it, and explore them recursively until all the references have been analysed. However, web services often produce dynamic responses which means that the content cannot be distinctly represented by its reference, i.e., the responses must be classified in a way that matches the users perception. The main problem is to find suitable criteria for this classification. This study describes how to make such a tool and it surveys ideas for how to create a classifying identifier for dynamic responses. The implemented spider was used to make experiments on selected web services, using different models for web node identification. The result is a proposal of suitable criteria for classification of dynamic responses, coming from web applications. These criteria are implemented in algorithms which use the parse structure and the set of internal references as the dominant terms of identification.

  • 5.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    On the Road to a Software Profession: Students' Experiences of Concepts and Thresholds2010Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Research has shown that there are gaps in knowledge between newly hired and experienced professionals and that some of these gaps are related to concepts, such as the concepts of object orientation. This problem, and the fact that most computer science majors want to work in the software industry, leads to questions regarding why these gaps exist and how students can be better prepared for their future careers. Against this background, this thesis addresses two theme-based perspectives that focus on students' views of concepts in Computer Science.

    The first theme-based perspective investigated the existence of potential Threshold Concepts in Computer Science. Such concepts should be troublesome, transformative, irreversible, and integrative. Qualitative methods have been mainly used and empirical data have been collected through semi-structured interviews, concept maps, and written stories. The results identified two Threshold Concepts, suggested several more, and then described the ways in which these concepts have transformed students.

    The second theme-based perspective took a phenomenographic approach to find the variation in how students understand concepts related to the software profession. Data were collected via semi-structured interviews. In one study the interviews were held in connection with role-playing where students took on the role of a newly hired programmer. The results show a variety of ways to experience the addressed phenomena in the student collective, ranging from superficial views that often have a practical nature to more sophisticated understandings that reflect a holistic approach, including a professional point of view.

    Educators can use the results to emphasize concepts that are important from students' perspectives. The phenomenographic outcome spaces can help teachers to reflect upon their own ways of seeing contrasted with student conceptions. I have indicated how variation theory can be applied to open more sophisticated ways of seeing, which in this context stresses the professional aspects to help students prepare for becoming professional software developers.

  • 6.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Students' different understandings of class diagrams2012In: Computer Science Education, ISSN 0899-3408, E-ISSN 1744-5175, Vol. 22, no 1, p. 29-62Article in journal (Refereed)
    Abstract [en]

    The software industry needs well-trained software designers and one important aspect of software design is the ability to model softwaredesigns visually and understand what visual models represent. However, previous research indicates that software design is a difficulttask to many students. This article reports empirical findings from aphenomenographic investigation on how students understand classdiagrams, Unified Modeling Language (UML) symbols, and relationsto object-oriented (OO) concepts. The informants were 20 Computer Science students from four different universities in Sweden. The results show qualitatively different ways to understand and describe UML class diagrams and the ‘‘diamond symbols’’ representing aggregation and composition. The purpose of class diagrams was understood in a varied way, from describing it as a documentation to a more advanced view related to communication. The descriptions of class diagrams varied from seeing them as a specification of classes to a more advanced view, where they were described to show hierarchic structures of classes and relations. The diamond symbols were seen as ‘‘relations’’ and a more advanced way was seeing the white and theblack diamonds as different symbols for aggregation and composition. As a consequence of the results, it is recommended that UML should be adopted in courses. It is briefly indicated how the phenomenographic results in combination with variation theory can be used by teachers to enhance students’ possibilities to reach advanced understanding of phenomena related to UML classdiagrams. Moreover, it is recommended that teachers should put more effort in assessing skills in proper usage of the basic symbols and models and students should be provided with opportunities to practise collaborative design, e.g. using whiteboards.

  • 7.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Students' Understanding of the Concept of Interface in a Situated Context2009In: Computer Science Education, ISSN 0899-3408, E-ISSN 1744-5175, Vol. 19, no 1, p. 15-36Article in journal (Refereed)
    Abstract [en]

    The paper describes an empirical study with the aim of producing insights about how students experience programming and software engineering. The research aims to investigate the students’ world, and hence, we have chosen a phenomenographic approach. Our questions focus on the students’ experience of concepts related to a realistic programming task in an extensive software system, particularly the Java Interface. The results show that there is a distinct variation of descriptions spanning from a concrete to-do list to a more advanced description where the interface plays a crucial role in order to produce dynamic and adaptive systems. We interpret the results and suggest how they can be used in teaching to provide an extended and varied understanding for how to work with advanced software.

  • 8.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Students working with a large software system: experiences and understandings2007Licentiate thesis, monograph (Other academic)
    Abstract [en]

    This monograph describes an empirical study with the overall aim of producing insights about how students experience the subject Computer Science and its learning environments, particularly programming and software engineering.

    The research takes a start in the students' world, from their perspective, using their stories, and hence, we have chosen a phenomenographic approach for our research. By interpreting the students' descriptions and experiences of various phenomena and situations, it is possible to gain knowledge about which different conceptions students can have and how teaching and the learning environment affect their understanding. In this study, we focus specifically on students' conceptions of aspects of object-oriented programming and their experiences of problem solving situations in connection with object-oriented system development.

    The questions posed enlighten and focus on the students' conceptions of both tangible and abstract concepts; the study investigates how students experienced a task concerning development in a specific software system, how they conceived the system itself, and how the students describe the system's plugin modules. Academic education in programming deals with abstract concepts, such as interfaces in the programming language Java. Hence, one of the questions in this study is how students describe that specific abstract concept, in a context where they are conducting a realistic software engineering task.

    The results show that there is a distinct variation of descriptions, spanning from a concrete to-do list, to a more advanced description where the interface plays a crucial role in order to produce dynamic and adaptive systems. The discussion interprets the results and suggests how we can use them in teaching to provide an extended and varied understanding, where the educational goal is to provide for and strengthen the conditions for students to be able to learn how to develop and understand advanced software.

  • 9.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Ways to Understand Class Diagrams2010Report (Other academic)
    Abstract [en]

    The software industry needs well trained software designers and one important aspect of software design is the ability to model software designs visually and understand what visual models represent. However, previous research indicates that software design is a difficult task to many students. This paper reports empirical findings from a phenomenographic investigation on how students understand class diagrams, UML symbols and relations to object oriented concepts. The informants were 20 Computer Science students from four different universities in Sweden.

    The results show qualitively different ways to understand and describe UML class diagrams and the "diamond symbols" representing aggregation and composition. The purpose of class diagrams was understood in a varied way, from describing it as a documentation to a more advanced view related to communication. The descriptions of class diagrams varied from seeing them as a specification of classes to a more advanced view where they were described to show hierarchic structures of classes and relations. The diamond symbols were seen as "relations" and a more advanced way was seeing the white and the black diamonds as different symbols for aggregation and composition.

    As a consequence of the results, it is recommended that UML should be adopted in courses. It is briefly indicated how the phenomenographic results in combination with variation theory can be used by teachers to enhance students' possibilities to reach advanced understanding of phenomena related to UML class diagrams. Moreover, it is recommended that teachers should put more effort in assessing skills in proper using of the basic symbols and models, and students should get many opportunities to practise collaborative design, e.g., using whiteboards.

  • 10.
    Boustedt, Jonas
    et al.
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Eckerdal, Anna
    McCartney, Robert
    Moström, Jan Erik
    Ratcliffe, Mark
    Sanders, Kate
    Zander, Carol
    Threshold concepts in computer science: do they exist and are they useful?2007In: SIGCSE Bulletin inroads, ISSN 0097-8418, Vol. 39, no 1, p. 504-508Article in journal (Other academic)
    Abstract [en]

    Yes, and Yes.

    We are currently undertaking an empirical investigation of “Threshold Concepts” in Computer Science, with input from both instructors and students. We have found good empirical evidence that at least two concepts—Object-oriented programming and pointers—are Threshold Concepts, and that there are potentially many more others.

    In this paper, we present results gathered using various experimental techniques, and discuss how Threshold Concepts can affect the learning process.

  • 11.
    Boustedt, Jonas
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    Uppsala Universitet.
    McCartney, Robert
    University of Connecticut, Storrs, CT, USA.
    Sanders, Kate
    Rhode Island College, Providence, RI, USA.
    Thomas, Lynda
    Aberystwyth University, Aberystwyth, Wales, UK.
    Zander, Carol
    University of Washington Bothell, Bothell, WA, USA .
    Students' perceptions of the differences between formal and informal learning2011In: ICER '11 Proceedings of the seventh international workshop on Computing education research / [ed] Kate Sanders, Michael Caspersen, Alison Clear, New York, USA: Association for Computing Machinery (ACM), 2011, p. 61-68Conference paper (Refereed)
    Abstract [en]

    Research has shown that most learning in the workplace takes place outside of formal training and, given the swiftly changing nature of the field, computer science graduates more than most workers, need to be able to learn computing topics outside of organized classes.

    In this paper we discuss students' perceptions of the difference between formal and informal learning of computing topics, based on three datasets: essays collected from a technical writing course at a single university; the results of a brainstorming exercise conducted in the same course; and semi-structured interviews conducted at six institutions in three countries.

    The students report strengths and weaknesses in informal learning. On the one hand, they are motivated, can choose their level of learning, can be more flexible about how they learn, and often retain the material better. On the other hand, they perceive that they may miss important aspects of a topic, learn in an ad hoc way, and have difficulty assessing their learning.

  • 12.
    Boustedt, Jonas
    et al.
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    McCartney, Robert
    Department of Computer Science and Engineering, University of Connecticut, United States.
    Deibel, Katherine
    Department of Computer Science and Engineering, University of Washington, Seattle, United States.
    Huggins, Jim
    Department of Computer Science, Kettering University, United States.
    Simon, Beth
    Department of Computer Science and Engineering, University of California San Diego, San Diego, United States.
    Westbrook, Suzanne
    Department of Computer Science, University of Arizona, Tucson, United States.
    It seemed like a good idea at the time2009In: SIGCSE '09: Proceedings of the 40th ACM technical symposium on Computer science education, New York, NY, USA: ACM , 2009, p. 265-266Conference paper (Refereed)
    Abstract [en]

    We often learn of successful pedagogical experiments, but we seldom hear of the the ones that failed. For this special session we solicited submissions from the SIGCSE membership, selected the best from among these, and will have presentations at the session by the selected authors. Our contributions describe pedagogical approaches that seemed to be good ideas but turned out as failures. At the session, contributors will describe their pedagogical experiment, the rationale for the experiment, evidence of failure, and lessons learned.

  • 13.
    Boustedt, Jonas
    et al.
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    McCartney, Robert
    University of Conneticut.
    Tenenberg, Josh
    University of Washington, Tacoma, United States.
    Anderson, Scott D.
    Wellesley College.
    Eastman, Caroline M.
    University of South Carolina.
    Garcia, Daniel D.
    University of California, Berkeley, United States.
    Gestwicki, Paul V.
    Ball State University.
    Menzin, Margaret S.
    Simmons college.
    It seemed like a good idea at the time2008In: SIGCSE '08: Proceedings of the 39th ACM Technical Symposium on Computer Science Education, 2008, p. 528-529Conference paper (Other academic)
    Abstract [en]

    We often learn of successful pedagogical experiments, but we seldom hear of the the ones that failed. For this special session we solicited submissions from the SIGCSE membership, selected the best from among these, and will have presentations at the session by the selected authors. Our contributions describe pedagogical approaches that seemed to be good ideas but turned out as failures. Contributors will describe their pedagogical experiment, the rationale for the experiment, evidence of failure, and lessons learned.

  • 14.
    Boustedt, Jonas
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    McCartney, Robert
    University of Connecticut, Storrs, CT, USA.
    Tenenberg, Josh
    University of Washington Tacoma, Tacoma, WA, USA.
    Cooper, Stephen
    Stanford University, Palo Alto, CA, USA.
    Garcia, Daniel, D.
    University of California Berkeley, Berkeley, CA, USA.
    Friend Hutton, Michelle
    Stanford University, Palo Alto, CA, USA.
    Parlante, Nick
    Stanford University, Palo Alto, CA, USA.
    Richards, Brad
    University of Puget Sound, Tacoma, WA, USA.
    It seemed like a good idea at the time2011In: SIGCSE'11: Proceedings of the 42nd ACM technical symposium on Computer science education, New York, NY, USA: ACM , 2011, p. 163-164Conference paper (Other academic)
    Abstract [en]

    We often learn of successful pedagogical experiments, but we seldom hear of the the ones that failed. For this special session we solicited submissions from the SIGCSE membership, selected the best from among these, and will have presentations at the session by the selected authors. Our contributions describe pedagogical approaches that seemed to be good ideas but turned out as failures. Contributors will describe their pedagogical experiment, the rationale for the experiment, evidence of failure, and lessons learned.

  • 15.
    Boustedt, Jonas
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    McCartney, Robert
    Department of Computer Science and Engineering, University of Connecticut, United States.
    Tenenberg, Josh
    Computing and Software Systems, University of Washington, Tacoma, WA, United States.
    Gehringer, F
    Department of Computer Science, North Carolina State University, United States.
    Lister, Raymond
    Faculty of Information Technology, University of Technology, Sydney, NSW, Australia.
    Musicant, Dave
    Department of Computer Science, Carleton College, United States.
    It seemed like a good idea at the time2010In: SIGCSE '10 : Proceedings of the 41th ACM technical symposium on Computer science education, New York: ACM , 2010, p. 558-559Conference paper (Other academic)
    Abstract [en]

    We often learn of successful pedagogical experiments, but we seldom hear of the the ones that failed. For this special session we solicited submissions from the SIGCSE membership, selected the best from among these, and will have presentations at the session by the selected authors. Our contributions describe pedagogical approaches that seemed to be good ideas but turned out as failures. Contributors will describe their pedagogical experiment, the rationale for the experiment, evidence of failure, and lessons learned.

  • 16.
    Boustedt, Jonas
    et al.
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    McCartney, Robert
    University of Connecticut.
    Tenenberg, Josh
    University of Washington, Tacoma, USA.
    Winters, Titus
    University of California, Riverside, USA.
    Edwards, Stephen
    Virginia Tech (VPI and SU), USA.
    Morrison, Briana B.
    So. Polytechnic St. University.
    Musicant, David R.
    Carleton College.
    Utting, Ian
    University of Kent, Canterbury, United Kingdom.
    Zander, Carol
    University of Washington, Bothell, USA.
    It seemed like a good idea at the time2007In: SIGCSE '07: Proceedings of the 38th SIGCSE technical symposium on Computer science education, 2007, p. 346-347Conference paper (Other academic)
    Abstract [en]

    We often learn of successful pedagogical experiments, but we seldom hear of the the ones that failed. From an epistemological point of view, learning from failures can be at least as effecitive as learning from good examples. This special session has a structure similar to that of Parlante’s Nifty Assignments, i.e. we solicited submissions from the SIGCSE membership, selected the best from among these, and have presentations at the session by the selected authors. Our contributions describe pedagogical approaches that seemed to be good ideas but turned out as failures. Contributors will describe their pedagogical experiment, the rationale for the experiment, evidence of failure, and lessons learned.

  • 17.
    Humble, Niklas
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Holmgren, Hanna
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Milutinovic, Goran
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Östberg, Ann-Sofie
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Cheaters or AI-Enhanced Learners: Consequences of ChatGPT for Programming Education2023In: Electronic Journal of e-Learning, E-ISSN 1479-4403Article in journal (Refereed)
    Abstract [en]

    Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant ChatGPT from OpenAI, many educators and stakeholders were both amazed and horrified by the potential consequences for education. One field with a potential high impact of ChatGPT is programming education in Computer Science (CS), where creating assessments has long been a challenging task due to the vast amount of programming solutions and support on the Internet. This now appears to have been made even more challenging with ChatGPT’s ability to produce both complex and seemingly novel solutions to programming questions. With the support of data collected from interactions with ChatGPT during the spring semester of 2023, this position paper investigates the potential opportunities and threats of ChatGPT for programming education, guided by the question: What could the potential consequences of ChatGPT be for programming education? This paper applies a methodological approach inspired by analytic autoethnography to investigate, experiment, and understand a novel technology through personal experiences. Through this approach, the authors have documented their interactions with ChatGPT in field diaries during the spring semester of 2023. Topics for the questions have related to content and assessment in higher education programming courses. A total of 6 field diaries, with 82 interactions (1 interaction = 1 question + 1 answer) and additional reflection notes, have been collected and analysed with thematic analysis. The study finds that there are several opportunities and threats of ChatGPT for programming education. Some are to be expected, such as that the quality of the question and the details provided highly impact the quality of the answer. However, other findings were unexpected, such as that ChatGPT appears to be “lying” in some answers and to an extent passes the Turing test, although the intelligence of ChatGPT should be questioned. The conclusion of the study is that ChatGPT have potential for a significant impact on higher education programming courses, and probably on education in general. The technology seems to facilitate both cheating and enhanced learning. What will it be? Cheating or AI-enhanced learning? This will be decided by our actions now since the technology is already here and expanding fast.

    Download full text (pdf)
    fulltext
  • 18.
    Humble, Niklas
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Holmgren, Hanna
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Milutinovic, Goran
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Seipel, Stefan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    Östberg, Ann-Sofie
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Computer and Geospatial Sciences, Computer Science.
    The consequences of ChatGPT for programming education: Cheating or AI-enhanced learning?2023In: Symposium on AI Opportunities and Challenges: Education will never be the same again, ACI Academic Conferences International, 2023, Vol. 1, p. 15-16Conference paper (Other academic)
    Abstract [en]

    Artificial Intelligence (AI) and related technologies have a long history of being used in education for motivating learners and enhancing learning. However, there have also been critiques for a too uncritical and naïve implementation of AI in education (AIED) and the potential misuse of the technology. With the release of the virtual assistant ChatGPT from OpenAI, many educators and stakeholders were both amazed and horrified by the potential consequences for education. One field with a potential high impact of ChatGPT is programming education in Computer Science (CS), where assessments have long been challenging due to the vast amount of programming solutions and support on the Internet. This now appears to have been made even more challenging with ChatGPT’s ability to produce both complex and seemingly novel solutions to programming questions. With the support of data collected from interactions with ChatGPT during the spring semester of 2023, a study was conducted where potential opportunities and threats of ChatGPT for programming education were investigated. The question to answer was: What will the consequences be for programming education? 

    The study applied a methodological approach inspired by action research and analytic autoethnography to investigate, experiment and understand a novel technology through personal experiences. Through this approach, the authors have documented their interactions with ChatGPT in field diaries during the spring semester of 2023. Topics for the questions have related to content and assessment in higher education programming courses. A total of 6 field diaries, with 82 interactions (1 interaction = 1 question + 1 answer) and additional reflection notes, have been collected and analysed with thematic analysis. 

    Findings of the study include several opportunities and threats of ChatGPT for programming education. Some are to be expected, such as that the quality of the question and the details provided highly impact the quality of the answer. However, other findings were unexpected, such as that ChatGPT appears to be lying in some answers and to an extent passes the Turing test, although the intelligence of ChatGPT should be questioned. The conclusion of the study is that ChatGPT will have a significant impact on higher education programming courses, and probably on education in general. The technology seems to facilitate both cheating and enhanced learning. What will it be? Cheating or AI-enhanced learning? This will be decided by our actions now since the technology is already here and expanding fast. 

  • 19. McCartney, Robert
    et al.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Eckerdal, Anna
    Moström, Jan-Erik
    Sanders, Kate
    Thomas, Lynda
    Zander, Carol
    Liminal Spaces and Learning Computing2009In: European Journal of Engineering Education, ISSN 0304-3797, E-ISSN 1469-5898, Vol. 34, no 4, p. 383-391Article in journal (Refereed)
    Abstract [en]

    “Threshold concepts” are concepts that, among other things, transform the way a student looks at a discipline. Although the term “threshold” might suggest that the transformation occurs at a specific point in time, an “aha” moment, it seems more common (at least in computing) that a longer time period is required. This time period is referred to as the “liminal space.”

    In this paper, we summarise our findings concerning how computing students experience the liminal space and discuss how this might affect teaching. Most of our findings so far relate to software engineering. As similar liminal spaces likely occur in other engineering disciplines, these findings have relevance across engineering education.

  • 20.
    McCartney, Robert
    et al.
    Computer Science and Engineering Department, University of Connecticut,, Storrs, CT, United States .
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    Information Technology, Department of Scientific Computing, Uppsala University, Uppsala, Sweden .
    Sanders, Kate
    Mathematics and Computer Science, Rhode Island College, Providence, RI, United States .
    Thomas, Lynda
    Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom .
    Zander, Carol
    Computing and Software Systems, University of Washington Bothell, Bothell, WA, United States .
    Why computing students learn on their own: motivation for self-directed learning of computing2016In: ACM Transactions on Computing Education, ISSN 1946-6226, E-ISSN 1946-6226, Vol. 16, no 1, article id 2Article in journal (Refereed)
    Abstract [en]

    In this article, we address the question of why computing students choose to learn computing topics on their own. A better understanding of why some students choose to learn on their own may help us to motivate other students to develop this important skill. In addition, it may help in curriculum design; if we need to leave some topics out of our expanding curriculum, a good choice might be those topics that students readily learn on their own.

    Based on a thematic analysis of 17 semistructured interviews, we found that computing students’ motivations for self-directed learning fall into four general themes: projects, social and peer interactions, joy of learning, and fear. Under these, we describe several more specific subthemes, illustrated in the words of the students.

    The project-related and social motivations are quite prominent. Although these motivations appear in theliterature, they received greater emphasis from our interviewees. Perhaps most characteristic of computingis the motivation to learn to complete some project, both projects done for fun and projects required for schoolor work.

  • 21.
    McCartney, Robert
    et al.
    Department of Computer Science and Engineering University of Connecticut Storrs, USA.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    Department of Information Technology Uppsala University Uppsala.
    Sanders, Kate
    Mathematics and Computer Science Department Rhode Island College Providence, USA.
    Zander, Carol
    Computing & Software Systems University of Washington Bothell Bothell, USA.
    Can first–year students program yet?: a study revisited2013In: ICER´13: Proceedings of the ninth International Conference on International Computing Education Research / [ed] Beth Simon, Alison Clear, Quintin Cutts, Association for Computing Machinery (ACM), 2013, p. 91-98Conference paper (Refereed)
    Abstract [en]

    Threshold concepts can be used to both organize disciplinaryknowledge and explain why students have diculties at cer-tain points in the curriculum. Threshold concepts transforma student's view of the discipline; before being learned, theycan block a student's progress.In this paper, we propose that in computing, skills, inaddition to concepts, can sometimes be thresholds. Somestudents report nding skills more dicult than concepts.We discuss some computing skills that may be thresholdsand compare threshold skills and threshold concepts.

  • 22.
    McCartney, Robert
    et al.
    Computer Science and Engineering, University of Connecticut, Storrs, CT, United States.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science. Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Eckerdal, Anna
    Department of Information Technology, Uppsala University, Uppsala, Sweden.
    Sanders, Kate
    Mathematics and Computer Science, Rhode Island College, Providence, RI, United States.
    Zander, Carol
    Computing and Software Systems, University of Washington Bothell, Bothell, WA, United States.
    Folk pedagogy and the geek gene: geekiness quotient2017In: Proceedings of the 2017 ACM SIGCSE Technical Symposium on Computer Science Education, NY, USA: ACM Digital Library, 2017, p. 405-410Conference paper (Refereed)
    Abstract [en]

    In a survey of the CS-education community, we find a range of beliefs about the "geek gene" theory. We suggest an alternative term, the "geekiness quotient (GQ)". The GQ, grounded in Gardner's work on multiple intelligences, is a hypothetical measure of the student's current CS ability. The GQ supports a moderate view of the geek gene: that students arrive in our classrooms with a range of CS abilities, whether acquired through background or innate talent, and can improve their abilities through effort.

  • 23. Moström, Jan Erik
    et al.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Eckerdal, Anna
    McCartney, Robert
    Sanders, Kate
    Thomas, Lynda
    Zander, Carol
    Concrete examples of abstraction as manifested in students’ transformative experiences2008In: ICER '08: proceedings of the fourth international workshop on Computing education research, New York: ACM , 2008, p. 125-136Conference paper (Refereed)
    Abstract [en]

    This paper examines transformational learning experiences of computing students as a way to better understand threshold concepts in computing. From empirical evidence we found that students often describe transformative experiences as learning situations in which they were led to use various kinds of abstraction, for example modularity, data abstraction, inheritance, polymorphism, reuse, design patterns, and complexity. Some students describe an abstract concept as coming first, and then needing to be made concrete though application; others describe transformations in which they learn the advantages of these abstract concepts from their experience of not using them.

    Abstraction is certainly of central importance in computer science. It appears, however, from our students’ descriptions of transformative experiences, that abstraction per se is not a threshold, but that particular concepts in which abstraction is paramount exhibit the characteristics of threshold concepts.

  • 24. Moström, Jan-Erik
    et al.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Eckerdal, Anna
    McCartney, Robert
    Sanders, Kate
    Thomas, Lynda
    Zander, Carol
    Computer Science Student Transformations: Changes and Causes2009In: ITiCSE'09: Proceedings of the 14th ACM–SIGCSE Annual Conference on Innovation and Technology in Computer Science Education, New York: ACM , 2009, p. 181-185Conference paper (Refereed)
    Abstract [en]

    We examine the transformations experienced by students during their study of computing. These transformations led to changes in the students’ perception of computing and in their behavior, confidence, and sense of identity as computing professionals. We discuss these transformations, their causes, and implications for the learning and teaching of computer science.

  • 25. Sanders, Kate
    et al.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Eckerdal, Anna
    McCartney, Robert
    Moström, Jan Erik
    Thomas, Lynda
    Zander, Carol
    Student understanding of object-oriented programming as expressed in concept maps2008In: SIGCSE Bulletin inroads, ISSN 0097-8418, Vol. 40, no 1, p. 332-336Article in journal (Refereed)
    Abstract [en]

    In this paper, we present the results of an experiment in which we sought to elicit students’ understanding of objectoriented (OO) concepts using concept maps. Our analysis confirmed earlier research indicating that students do not have a firm grasp on the distinction between “class” and “instance.” Unlike earlier research, we found that our students generally connect classes with both data and behavior. Students rarely included any mention of the hardware/software context of programs, their users, or their real-world domains. Students do mention inheritance, but not encapsulation or abstraction. And the picture they draw of OO is a static one: we found nothing that could be construed as referring to interaction among objects in a program. We then discuss the implications for teaching introductory OO programming.

  • 26. Sanders, Kate
    et al.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    McCartney, Robert
    Moström, Jan Erik
    Thomas, Lynda
    Zander, Carol
    Threshold concepts and threshold skills in computing2012In: Proceedings of the ninth annual international conference on International computing education research, New York, NY, USA: Association for Computing Machinery (ACM), 2012, p. 23-30Conference paper (Refereed)
    Abstract [en]

    Threshold concepts can be used to both organize disciplinary knowledge and explain why students have difficulties at certain points in the curriculum. Threshold concepts transform a student's view of the discipline; before being learned, they can block a student's progress.

    In this paper, we propose that in computing, skills, in addition to concepts, can sometimes be thresholds. Some students report finding skills more difficult than concepts. We discuss some computing skills that may be thresholds and compare threshold skills and threshold concepts.

  • 27.
    Sanders, Kate
    et al.
    Rhode Island College, Providence, Rhode Island, USA.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    Uppsala University, Uppsala, Sweden.
    McCartney, Robert
    University of Connecticut, Storrs, Connecticut, USA.
    Zander, Carol
    University of Washington, Bothell Bothell, Washington, USA.
    Folk Pedagogy: Nobody Doesn't Like Active Learning2017In: Proceedings of the 2017 ACM Conference on International Computing Education Research (ICER 17) / [ed] Josh Tenenberg and Lauri Malmi, Tacoma, Washington, USA: ACM Publications, 2017, p. 145-154Conference paper (Refereed)
    Abstract [en]

    In a survey of the computing education community, many respondents suggested "active learning" as a teaching approach that would increase the likelihood of student success. In light of these responses, we analyze the way in which active learning is described in the computing-education literature. We find a strong consensus that active learning is good, but a lack of precision in how the term is used, often without definition, to describe instructional techniques, rather than student learning. In addition, active learning techniques are often discussed as if they were all equally effective. We suggest that making clear distinctions, both between teaching techniques and active learning and among the teaching techniques, would be fruitful for both instructors and researchers. Finally, we propose some dimensions along which distinctions among techniques could usefully be made.

  • 28.
    Thomas, Lynda
    et al.
    Aberystwyth University, Great Britain.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    Uppsala University.
    McCartney, Robert
    University of Connecticut, USA.
    Moström, Jan-Erik
    Umeå University,.
    Sanders, Kate
    Rhode Island College, USA.
    Zander, Carol
    University of Washington, USA.
    A broader threshold: Including skills as well as concepts in computing education2014In: Threshold Concepts: From personal practice to communities of practice: Proceedings of the National Academy’s Sixth Annual Conference and the Fourth Biennial Threshold Concepts Conference / [ed] Catherine O´Mahony, Aril Buchanan,Mary O´Rourke, Bettie Higgs, Cork, Ireland: NAIRTL , 2014, p. 154-158Conference paper (Refereed)
    Abstract [en]

    We propose ‘threshold skills’ as a complement to threshold concepts. The definition of threshold concepts assumes that theoretical knowledge is paramount: gaining the understanding of particular concepts irreversibly transforms the learners.

    Mastering computing, like many disciplines, however, requires learning a combination of concepts and skills. Mathematicians learn to do proofs, musicians learn to play their instruments, and martial artists learn to make moves by doing these activities, not just intellectually understanding them. We propose some characteristics for threshold skills and outline implications for teaching and for future work.

  • 29.
    Thomas, Lynda
    et al.
    Computer Science, Aberystwyth University , UK.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    Department of Information Technology, Uppsala University, Sweden.
    McCartney, Robert
    Department of Computer Science and Engineering University of Connecticut, USA.
    Moström, Jan-Erik
    Department of Computing Science, Umeå University , Sweden.
    Sanders, Kate
    Mathematics and Computer Science Department ,Rhode Island College, USA.
    Zander, Carol
    Computing & Software Systems, University of Washington Bothell , USA.
    In the liminal space: software design as a threshold skill2017In: Practice and Evidence of the Scholarship of Teaching and Learning in Higher Education, E-ISSN 1750-8428, Vol. 12, no 2, p. 333-351Article in journal (Refereed)
    Abstract [en]

    In previous work we proposed the idea of ‘threshold skills’ as a complement to threshold concepts. The definition of threshold concepts assumes that theoretical knowledge is paramount: gaining the understanding of particular concepts irreversibly transforms the learners. We noted, however, that mastering computing, like many disciplines, requires learning a combination of concepts and skills, and we suggested that this required further investigation. In this paper we examine the activity of designing software as a possible example of such a threshold skill. We looked at 35 software designs collected from students nearing graduation in computing courses, and see many of the characteristics of threshold skill and also of students being in liminal space. A close examination of the students’ designs leads to some useful implications for teaching this fundamental activity.

  • 30. Thomas, Lynda
    et al.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, Anna
    McCartney, Robert
    Moström, Jan-Erik
    Sanders, Kate
    Zander, Carol
    Threshold concepts in computer science: an ongoing empirical investigation2010In: Threshold concepts and transformational learning / [ed] Jan H. F. Meyer, Ray Land, Caroline Baillie, Rotterdam: Sense Publishers , 2010, p. 241-258Chapter in book (Other academic)
    Abstract [en]

    The chapter describes an ongoing multi-national, multi-institutional project aimed at empirically identifying threshold concepts in Computer Science, and describing students’ experiences of learning these concepts.

  • 31.
    Viirman, Olov
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Mathematics.
    Pettersson, Irina
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Mathematics.
    Björklund, Johan
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Electrical Engineering, Mathematics and Science, Mathematics.
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Programming in mathematics teacher education: A collaborative teaching approach2018Conference paper (Refereed)
  • 32.
    Zander, C.
    et al.
    Computing and Software Systems, University of Washington Bothell, Bothell, WA, United States .
    Boustedt, Jonas
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Computer science.
    Eckerdal, A.
    Department of InformationTechnology, Uppsala University, Uppsala, Sweden .
    Mccartney, R.
    Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, United States .
    Moström, J. E.
    Department of Computing Science, Umeå University, Umeå, Sweden .
    Sanders, K.
    Mathematics and Computer Science Department, Rhode Island College, Providence, RI, United States .
    Thomas, L.
    Department of Computer Science, Aberystwyth University, Aberystwyth, United Kingdom .
    Self-directed learning: Stories from industry2012In: Proceedings - 12th Koli Calling International Conference on Computing Education Research, Koli Calling 2012, 2012, p. 111-117Conference paper (Refereed)
    Abstract [en]

    We report preliminary results from an ongoing investigation of how computing professionals perceive and value selfdirected learning, based on a qualitative analysis of interviews with ten computing professionals. The professionals expect that future colleagues will have a well-developed ability to learn on their own. They indicate that professionals use a range of resources, strategies, and collaborators to help them learn. They find their work-related self-directed learning enjoyable, expressing a sense of confidence and pride; yet they often also find it to be a stressful never-ending process.

  • 33. Zander, Carol
    et al.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    Eckerdal, Anna
    McCartney, Robert
    Moström, Jan-Erik
    Ratcliffe, Mark
    Sanders, Kate
    Threshold concepts in computer science: a multi-national empirical investigation2008In: Threshold concepts within the disciplines / [ed] Ray Land, Jan H. F. Meyer, Jan Smith, Rotterdam: Sense , 2008, p. 105-118Chapter in book (Other academic)
    Abstract [en]

    This chapter describes an ongoing project aimed at empirically identifying threshold concepts in computer science. In a multi-national, multi-institutional study, we have gathered data from both educators and students. The paper outlines our experiences with various experimental techniques, issues raised, and results to date.

  • 34.
    Zander, Carol
    et al.
    University of Washington, Bothell, Bothell, WA, USA.
    Boustedt, Jonas
    University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för datavetenskap.
    McCartney, Robert
    University of Connecticut, Storrs, CT, USA.
    Moström, Jan-Erik
    Umeå University, Umeå, Sweden.
    Sanders, Kate
    Rhode Island College, Providence, RI, USA.
    Thomas, Lynda
    Aberystwyth University, Aberystwyth, Wales Uk.
    Student transformations: are they computer scientists yet?2009In: ICER '09: Proceedings of the fifth international workshop on Computing education research, New York: ACM , 2009, p. 129-140Conference paper (Refereed)
    Abstract [en]

    We examine the changes in the ways computing students view their field as they learn, as reported by the students themselves in short written biographies. In many ways, these changes result in students thinking and acting more like computer scientists and identifying more with the computing community. Most of the changes are associated with programming and software engineering, rather than theoretical computer science, however.

1 - 34 of 34
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