Petri Ihantola

Bio: Petri Ihantola is an academic researcher from University of Helsinki. The author has contributed to research in topics: Educational data mining & Computer science. The author has an hindex of 21, co-authored 65 publications receiving 1795 citations. Previous affiliations of Petri Ihantola include Tampere University of Technology & Aalto University.

Review of recent systems for automatic assessment of programming assignments

Abstract: This paper presents a systematic literature review of the recent (2006--2010) development of automatic assessment tools for programming exercises. We discuss the major features that the tools support and the different approaches they are using both from the pedagogical and the technical point of view. Examples of these features are ways for the teacher to define tests, resubmission policies, security issues, and so forth. We have also identified a list of novel features, like assessing web software, that are likely to get more research attention in the future. As a conclusion, we state that too many new systems are developed, but also acknowledge the current reasons for the phenomenon. As one solution we encourage opening up the existing systems and joining efforts on developing those further. Selected systems from our survey are briefly described in Appendix A.

Educational Data Mining and Learning Analytics in Programming: Literature Review and Case Studies

Abstract: Educational data mining and learning analytics promise better understanding of student behavior and knowledge, as well as new information on the tacit factors that contribute to student actions. This knowledge can be used to inform decisions related to course and tool design and pedagogy, and to further engage students and guide those at risk of failure. This working group report provides an overview of the body of knowledge regarding the use of educational data mining and learning analytics focused on the teaching and learning of programming. In a literature survey on mining students' programming processes for 2005-2015, we observe a significant increase in work related to the field. However, the majority of the studies focus on simplistic metric analysis and are conducted within a single institution and a single course. This indicates the existence of further avenues of research and a critical need for validation and replication to better understand the various contributing factors and the reasons why certain results occur. We introduce a novel taxonomy to analyse replicating studies and discuss the importance of replicating and reproducing previous work. We describe what is the state of the art in collecting and sharing programming data. To better understand the challenges involved in replicating or reproducing existing studies, we report our experiences from three case studies using programming data. Finally, we present a discussion of future directions for the education and research community.

Predicting academic performance: a systematic literature review

Abstract: The ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a clearly increasing amount of research in this area, as well as an increasing variety of techniques used. At the same time, the review uncovered a number of issues with research quality that drives a need for the community to provide more detailed reporting of methods and results and to increase efforts to validate and replicate work.

How (not) to introduce badges to online exercises

Abstract: Achievement badges are increasingly used to enhance educational systems and they have been shown to affect student behavior in different ways. However, details on best practices and effective concepts to implement badges from a non-technical point of view are scarce. We implemented badges to our learning management system, used them on a large course and collected feedback from students. Based on our experiences, we present recommendations to other educators that plan on using badges.

Eye tracking in computing education

Abstract: The methodology of eye tracking has been gradually making its way into various fields of science, assisted by the diminishing cost of the associated technology. In an international collaboration to open up the prospect of eye movement research for programming educators, we present a case study on program comprehension and preliminary analyses together with some useful tools.The main contributions of this paper are (1) an introduction to eye tracking to study programmers; (2) an approach that can help elucidate how novices learn to read and understand programs and to identify improvements to teaching and tools; (3) a consideration of data analysis methods and challenges, along with tools to address them; and (4) some larger computing education questions that can be addressed (or revisited) in the context of eye tracking.

Why most published research findings are false

Abstract: There is increasing concern that most current published research findings are false. The probability that a research claim is true may depend on study power and bias, the number of other studies on the same question, and, importantly, the ratio of true to no relationships among the relationships probed in each scientific field. In this framework, a research finding is less likely to be true when the studies conducted in a field are smaller; when effect sizes are smaller; when there is a greater number and lesser preselection of tested relationships; where there is greater flexibility in designs, definitions, outcomes, and analytical modes; when there is greater financial and other interest and prejudice; and when more teams are involved in a scientific field in chase of statistical significance. Simulations show that for most study designs and settings, it is more likely for a research claim to be false than true. Moreover, for many current scientific fields, claimed research findings may often be simply accurate measures of the prevailing bias. In this essay, I discuss the implications of these problems for the conduct and interpretation of research.

Gamification in Education: A Systematic Mapping Study

Abstract: Introduction Traditional schooling is perceived as ineffective and boring by many students. Although teachers continuously seek novel instructional approaches, it is largely agreed that today's schools face major problems around student motivation and engagement (Lee & Hammer, 2011). The use of educational games as learning tools is a promising approach due to the games' abilities to teach and the fact that they reinforce not only knowledge but also important skills such as problem-solving, collaboration, and communication. Games have remarkable motivational power; they utilize a number of mechanisms to encourage people to engage with them, often without any reward, just for the joy of playing and the possibility to win. Creating a highly engaging, full-blown instructional game however is difficult, time consuming, and costly (Kapp, 2012a), while typically targeting only a single set of learning objectives as chosen by the game designer. In addition, their effective classroom adoption requires certain technical infrastructure and appropriate pedagogical integration. As opposed to using elaborate games requiring a large amount of design and development efforts, the "gamification" approach suggests using game thinking and game design elements to improve learners' engagement and motivation. Gamification, defined by Deterding et al. (2011) as the use of game design elements in non-game contexts, is a fairly new and rapidly growing field. The concept of gamification is different from that of an educational or serious game. While the latter describes the design of full-fledged games for non-entertainment purposes, "gamified" applications merely employ elements of games. The term "gamification" is quite recent: According to (Deterding et al., 2011) its first documented use is in 2008 but it did not see widespread adoption before the second half of 2010. Nevertheless, the concept itself is not new. For example, badges and ranks have been long used in the military, in the early Soviet era, game elements were used by the Soviet Union leaders as a substitute for monetary incentives for performing at work, etc. In recent years gamification has seen rapid adoption in business, marketing, corporate management, and wellness and ecology initiatives. This is driven by its potential to shape users' behavior in a desirable direction. Loyalty programs such as the frequent-flyer programs, Foursquare, and Nike+ are often given as examples of successful gamified mass-market products. Stackoverflow.com provides another example in which users' reputations increase as they answer questions and receive votes for their answers. Online education sites such as codeacademy.com and khanacademy.org use game elements to better engage users. The more courses and lessons that users complete, the more badges they earn. Sites like eBay and Fitocracy use game elements to keep people engaged and to encourage friendly competition between users. Gamification is still rising in popularity. According to Gartner's Hype Cycle (Gartner, 2013), a research methodology that outlines an emerging technology's viability for commercial success, gamification is at the peak of the Hype Cycle in 2013, with an expectation for reaching the productivity plateau in five to ten years. This position, however, mainly reflects its use in business contexts. The penetration of the gamification trend in educational settings seems to be still climbing up to the top, as indicated by the amount and annual distribution of the reviewed works. This paper presents the results of a study of the published works on the application of gamification to education, which aims to shed light on the tendencies and emerging practices in this area. There are few literature reviews on gamification (see Xu, 2012; Hamari, Koivisto, & Sarsa, 2014; Nah, Zeng, Telaprolu, Ayyappa, & Eschenbrenner, 2014), with only the last one focusing on education. This study differs from the latter by presenting a thematic analysis instead of narrative summaries that focus on a qualitative review. …

Teaching for quality learning at university

Abstract: by J. Biggs and C. Tang, Maidenhead, England, Open University Press, 2007, 360 pp., £29.99, ISBN-13: 978-0-335-22126-4

Review of recent systems for automatic assessment of programming assignments

Abstract: This paper presents a systematic literature review of the recent (2006--2010) development of automatic assessment tools for programming exercises. We discuss the major features that the tools support and the different approaches they are using both from the pedagogical and the technical point of view. Examples of these features are ways for the teacher to define tests, resubmission policies, security issues, and so forth. We have also identified a list of novel features, like assessing web software, that are likely to get more research attention in the future. As a conclusion, we state that too many new systems are developed, but also acknowledge the current reasons for the phenomenon. As one solution we encourage opening up the existing systems and joining efforts on developing those further. Selected systems from our survey are briefly described in Appendix A.