Timo Hynninen

Towards Interoperability in Video Games

In this paper we investigate the possibility how to enable transfer of meaningful game information between different video games. We explore the benefits of ontologies as a solution to this problem, and present an initial version of Game Ontology, a first step towards achieving interoperability between games.

Guidelines for software testing education objectives from industry practices with a constructive alignment approach

Testing and quality assurance are characterized as the most expensive tasks in the software life cycle. However, several studies also indicate that the industry could enhance product quality and reduce costs by investing in developing testing practices. Software engineering educators can bridge the gap between formal education and industry practices to produce more industry-ready graduates, by observing the industry in action. To find out the current state of industry, we conducted a study in software organizations to assess how they test their products and which process models they follow. According to the survey results, the organizations rely heavily on test automation and use sophisticated testing infrastructures, apply agile practices even when working with mission-critical software, and have reduced the use of formal process reference and assessment models. Based on the results, this paper identifies a number of key learning objectives in quality assurance and software testing disciplines that the industry expects from university graduates. The principles of constructive alignment are used to present learning goals, teaching methods, and assessment methods that align with the industry requirements.

Taxonomizing features and methods for identifying at-risk students in computing courses

Since computing education began, we have sought to learn why students struggle in computer science and how to identify these at-risk students as early as possible. Due to the increasing availability of instrumented coding tools in introductory CS courses, the amount of direct observational data of student working patterns has increased significantly in the past decade, leading to a flurry of attempts to identify at-risk students using data mining techniques on code artifacts. The goal of this work is to produce a systematic literature review to describe the breadth of work being done on the identification of at-risk students in computing courses. In addition to the review itself, which will summarize key areas of work being completed in the field, we will present a taxonomy (based on data sources, methods, and contexts) to classify work in the area.

Plagiarism networks: finding instances of copied answers in an online introductory programming environment

We followed the submissions of automatically evaluated weekly programming assignments on an introductory programming course and searched for identical solutions submitted by students. Our dataset covers three iterations of the course, from 2014 to 2016. From this systematic longitudinal sampling, we were able to scan for plagiarism patterns and build social networks of shared answers. As a result, we present the social networking graphs of identical student-submitted answers over the past three years in which the course has been arranged.