11 Dec 2016
Figure: A Three Cycle view of Design Science Research Process (Hevner, 2007)
My recently defended doctoral thesis on computer-supported collaborative work is now available online. The application domain in university level engineering education, and gamification is one of the major methods I investigated and applied. The thesis also includes a rather thorough use of the design science methodology in design, implementation cycles and validation.
Find the PDF available for free from the Doria library archive.
Knutas, A. (2016). Increasing Beneficial Interactions in a Computer-Supported Collaborative Environment. Acta Universitatis Lappeenrantaensis.
Publications included in the thesis
- Knutas, A., Ikonen, J., & Porras, J. (2013). Communication patterns in collaborative software engineering courses: a case for computer-supported collaboration. In Proceedings of the 13th Koli Calling International Conference on Computing Education Research (pp. 169-177). ACM. Preprint from ResearchGate.
- Knutas, A., Ikonen, J., & Porras, J. (2015). COMPUTER-SUPPORTED COLLABORATIVE LEARNING IN SOFTWARE ENGINEERING EDUCATION: A SYSTEMATIC MAPPING STUDY. International Journal on Information Technologies & Security, 7(4). IJITS Archive. Preprint from ResearchGate.
- Ikonen, J., Knutas, A., Wu, Y., & Agudo, I. (2015, November). Is the world ready or do we need more tools for programming related teamwork?. In Proceedings of the 15th Koli Calling Conference on Computing Education Research (pp. 33-39). ACM. Preprint from ResearchGate.
- Knutas, A., Ikonen, J., Nikula, U., & Porras, J. (2014, June). Increasing collaborative communications in a programming course with gamification: a case study. In Proceedings of the 15th International Conference on Computer Systems and Technologies (pp. 370-377). ACM. Preprint from ResearchGate.
- Knutas, A., Ikonen, J., Maggiorini, D., Ripamonti, L., & Porras, J. (2016). Creating Student Interaction Profiles for Adaptive Collaboration Gamification Design. International Journal of Human Capital and Information Technology Professionals (IJHCITP), 7(3), 47-62. DOI: 10.4018/IJHCITP.2016070104. IGI Global.
University and software engineering teaching are changing in response to the industry demand for new skills. Learning is becoming more interactive, and the impact of student collaborative learning has increased. The extension of collaboration with computer-supported collaborative environments allows increased knowledge building between a wider range of participants. More flexible teaching structures independent of place or time, better monitoring of student understanding by instructors, and improved student productivity and satisfaction can also be facilitated. However, the collaboration has to be implemented carefully, or it will become a drawback instead of a benefit. The first objective of this study is to document the current state of the utilization of collaborative environments and methods in software engineering education.
The next stage is to use the results to first specify the requirements for a computer-supported collaborative environment, then to design and implement a prototype, and finally to use this prototype to evaluate and validate the design for improved collaboration. The research follows the design science research process, where a solution design is created through an iterative design and evaluation process and the solution is validated through its utility. A design for improving collaboration by improving issue-related and inter-team communication is created. The collaboration is promoted further by applying gamification to the design. The study shows that engineering students can be encouraged to collaborate online with the application of gamification, that the system increases connectivity in collaboration patterns, and in some cases this collaboration has positive results for learning goals. During the research, the state of gamification design for computer-supported collaboration was developed further by connecting it with the theory of player profiles. Different types of players respond best to different kinds of rewards, for example a simulated social status or additional challenges instead of just an increased score. This study also presents a method for creating gamification profiles from empirical observations in collaborative learning environments.
24 Aug 2016
Figure: Bartle’s Taxonomy of Player Types (1996)
Gamification is a hot topic in research and it has been widely applied to the web. However, it is not a magic bullet for user engagement and we propose that there can be a better approach than a “one size fits all” design. Our solution is to define several different user profiles and adaptively apply them for different types of users. For example, one type of person might like having most points and being on the top of the high score and another type of user might enjoy exploring new solutions and sharing with them with the community. Both types of users might do the same activity, but their internal motivation for enjoying the activity are different. The challenge in this approach is to detect the type of user and then adaptively present the right gamification elements to each type of user.
We used an evidence-based method for deciding which gamification elements to apply and how to apply them. In order to do this we built behavior profiles with interaction analysis and profiling surveys. These profiles can be used match types of user to most suitable gamification and game design elements in order to create or improve adaptive gamification systems.
We discovered four types of activitiy profiles, compared them with Bartle types (2004) and matched them with formal elements of game design (Fullerton, 2008) that might be most attractive to each cluster. These profiles can be used to design adaptive gamification approaches, especially for online collaborative systems.
Read more at the IJHCITP journal website. Unfortunately this time the licensing restriction prohibited publishing a pre-print version. If your library does not subscribe to IJHCITP and you still want to view the results, please contact me on Twitter or ResearchGate and we will figure out a solution.
We used Social Network Analysis and K-Means clustering to construct the profiles. There is a Prezi presentation from a previous study that visualizes some of the data collection methods.
Benefits of collaborative learning are established and gamification methods have been used to motivate students towards achieving course goals in educational settings. However, different users prefer different game elements and rewarding approaches and static gamification approaches can be inefficient. We present an evidence-based method and a case study where interaction analysis and k-means clustering are used to create gamification preference profiles. These profiles can be used to create adaptive gamification approaches for online learning or collaborative learning environments, improving on static gamification designs. Furthermore, we discuss possibilities for using our approach in collaborative online learning environments.
Below you can find a list of the activity clusters we discovered, with the corresponding Bartle player types and formal game elements that could be applied to each cluster.
Table: Discovered Profile Clusters
| Profile cluster
|| Exhibited Bartle player types
|| Most applicable game elements
|CL1: “Cooperative workers”
||Formal elements: Player interaction, rules, conflict, outcomes. Dramatic elements: Character, challenge, play.
|CL2: “Social team members”
||Heart, club, spade
||Formal elements: Player interaction, rules, resources, boundaries, outcomes. Dramatic elements: Premise, story, character, challenge, play.
|CL3: “Achievement-oriented leaders”
||Formal elements: Player interaction, rules, procedures, conflict, boundaries, outcomes. Dramatic elements: Challenge, play.
|CL4: “Task-oriented workers”
||Diamond, club, spade
||Formal elements: Rules, conflict, resources, outcomes. Dramatic elements: Premise, challenge, play.
Knutas, A., Ikonen, J., Maggiorini, D., Ripamonti, L., & Porras, J. (2016). Creating Student Interaction Profiles for Adaptive Collaboration Gamification Design. International Journal of Human Capital and Information Technology Professionals (IJHCITP), 7(3), 47-62. DOI: 10.4018/IJHCITP.2016070104
12 Jul 2016
We have published our full case study and recommendations for applying flipped classroom in teaching programming at university level. Flipped classroom is a teaching method where students first study theory by themselves as a pre-assigned homework and then learn in the classroom by working on exercises. This is the opposite of the traditional “listen at class and then work alone at home” approach, hence the term “flipped”. This approach aims to maximize the usefulness of the time the teacher and the students spend together.
To summarize, in the paper we published the following recommendations:
- Create or curate videos in addition to text-based material
- Video curating suggested, if the instructor intends to hold small lectures
- Use weekly quizzes to evaluate the level of understanding and satisfaction
- Strictly integrate the theory and material to the course
- Encourage students to engage peers in-class and to review each other’s work
- Require students to start the weekly tasks before the exercises as preparatory work
Read the conference paper in ACM Digital Library (preprint) or see the presentation slides. There’s also a poster from our previous conference presentation.
The flipped classroom teaching method, which emphasizes independent learning of theory and practical, in-depth exercises in the classroom, is gaining foothold in teaching. The method is increasingly being applied at university level. It has been implemented with varying approaches and guidelines, and a single unified process has not been described. In this article we compare existing literature to two case studies where flipped classroom was introduced to teaching. We discuss the lessons learned in these cases and present recommendations based on our experiences. Flipping the classroom has been found to be more efficient than traditional lecture-exercises method and the findings in this study support this. Therefore we recommend teachers to explore the possibility of utilizing the flipped classroom method in their courses.
06 Jul 2016
Figure: Most Common Keywords in Patents Related to Online Gaming
In a recent research project initiated by my colleague the NAILS project was extended to analyse and compare the other major database indexing science and technology results, patents. These results were recently published in a conference and now the preprint is available for your perusal. This is exciting (for a certain definition of exciting), because previously there has not been a freely available bibliometric analysis tool to map and visualize patent data. For now you also need a subscription to Web of Science to download patent metadata for analysis.
Preprint is available in ResearchGate.
In this paper, we present an analysis method that allows the combination of multiple data sources by extending the NAILS bibliometric cloud service, with the focus on the development of a novel cloud-based online infrastructure that enables the user to compare scientific literature and patent data related to a particular technology domain. This cloud-based tool leverages meta-data analysis and text-mining techniques to visualize the semi-structured patent and journal articles data stored on Web of Science database. The designed cloud-based tool can automate the process of patent landscape visualization, scientific literature mapping and provides an independent interface for comparing patent and paper trends on a specific subject. The implementation demonstrates how a flexible plugin system can benefit tools by introducing new data sources. We also present a roadway to fully realize a service oriented analysis service for utilizing open data and discuss the steps required to realize this vision.
30 Jun 2016
Figure: Unity Development Environment
There are many approaches to teaching the basics of programming from traditional lecture-type teaching in universities to interactive courses (CodeCademy) to MOOCs (mooc.fi). I recently taught a basics of programming course to teens, arranged by the local center of STEM education, LUMA. The course lasted for five days with the goal of introducing complete novices to the basics of programming (variables, control structures, loops) and the basics of game development.