TY - CHAP A1 - Reuter, Rebecca A1 - Hauser, Florian A1 - Gold-Veerkamp, Carolin A1 - Mottok, Jürgen A1 - Abke, Jörg T1 - Towards a Definition and Identification of Learning Obstacles in Higher Software Engineering Education T2 - EDULEARN17 Proceedings, 9th International Conference on Education and New Learning Technologies, 3-5 July, 2017, Barcelona, Spain KW - Hochschuldidaktik KW - Software Engineering Y1 - 2017 SN - 978-84-697-3777-4 U6 - https://doi.org/10.21125/edulearn.2017.0943 SN - 2340-1117 SP - 10259 EP - 10267 ER - TY - CHAP A1 - Nivala, Markus A1 - Hauser, Florian A1 - Jossberger, Helen A1 - Reiß, Markus A1 - Mottok, Jürgen A1 - Gruber, Hans T1 - Detecting errors in program flow diagrams: Comparing novices and advanced programmers T2 - EARLI Biennial Conference 2017, 17th European Association for Research on Learning and Instruction, 29 August - 2 September, 2017 - University of Tampere, Finland Y1 - 2017 ER - TY - CHAP A1 - Reuter, Rebecca A1 - Hauser, Florian A1 - Gold-Veerkamp, Carolin A1 - Stark, Theresa A1 - Kis, Juliane A1 - Mottok, Jürgen A1 - Abke, Jörg A1 - Meyer, Dany T1 - Towards the construction of a questionnaire for the identification of learning obstacles T2 - 2018 IEEE Global Engineering Education Conference (EDUCON 2018), 17-20 April, 2018, Santa Cruz de Tenerife, Spain N2 - This paper deals with the identification of learning ob-stacles using the questionnaire method. Therefore, two iterations were proceeded: The first one was part of a survey that was carried out at four lo-cations at universities of applied sciences. We asked students about obstructive facts in general providing items for five learning ob-stacle dimensions that were set up before; emotional/motivational, epistemological/cognitive, didactical, resource-related and meta-cognitive learning obstacle dimensions. After the general part, we asked them to answer the same question, but in relation to the – in their opinion – most difficult learning content. With this question, we aim to get indications regarding to epistemological obstacles. In a second step, we used the “Motivated Strategies for Learning Questionnaire”, which was developed by Pintrich [1] as a basis to develop a questionnaire that extracts learning obstacles. In its original version, the “Motivated Strategies for Learning Question-naire” was intended to measure students’ learning strategies, but, as the obstacle dimensions were partly derived from learning strategy classification, we chose this already validated question-naire [2]. Within this iteration, we could confirm a five-factor structure of the questionnaire that could be mapped to the five be-fore set learning obstacle dimensions. Y1 - 2018 U6 - https://doi.org/10.1109/EDUCON.2018.8363266 SP - 457 EP - 466 ER - TY - CHAP A1 - Hauser, Florian A1 - Reuter, Rebecca A1 - Gruber, Hans A1 - Mottok, Jürgen T1 - Research competence: Modification of a questionnaire to measure research competence at universities of applied sciences T2 - IEEE Global Engineering Education Conference (EDUCON), 17-20 April 2018, Santa Cruz de Tenerife, Spain N2 - This paper deals with the validation and modification of the German questionnaire "F-Komp". In its original version, it was intended to measure university students' research competences. In the beginning of this study, there were only a few tools available which were reliable. For the purposes of this study, they were not suitable. At the same time, there was no validated version of the F-Komp available, which made the whole validation process for further usage necessary. This questionnaire is based on a structure, which consist of different skills and knowledge and is focused on measuring research competence in general. The validation and modification of the F-Komp is therefore the aim of our contribution as well as a revised version of the questionnaire. We proceeded an explorative factor and a reliability analysis to do a general evaluation of the tool. Some modifications were done in the questionnaire to make it more suitable to the requirements of technical oriented universities of applied sciences [5]. Our revised version is slightly longer and contains several items to gather data about the participants demographics. The modified questionnaire is based on a more appropriate factor structure. This structure is more practically oriented and pays attention to ethical issues. In future cases, this questionnaire will be used in research oriented courses to measure students' progress in acquiring the knowledge and methods which are necessary to perform as a scientist in different research areas. KW - research oriented teaching KW - research competence KW - competence model KW - modification of a questionnaire Y1 - 2018 U6 - https://doi.org/10.1109/EDUCON.2018.8363216 SP - 109 EP - 117 ER - TY - CHAP A1 - Hauser, Florian A1 - Gegenfurtner, Andreas A1 - Hutzler, Ivonne A1 - Reuter, Rebecca A1 - Mottok, Jürgen T1 - Eye movement patterns in source code review T2 - EARLI SIG 17 and 25 Biennial Conference 2018, Cambridge, United Kingdom N2 - This study is based on the work of Uwano, Nakamura, Monden and Matsumoto (2006) who tried to identify programmers’ eye movements in source code reviews by using eye tracking technology. The researchers were able to identify certain eye movement patterns but due to the technical limitations of earlier eye tracking systems and a small sample they could not find a valid proof for their existence. Now, twelve years later, the eye tracking technology has made significant improvements and is able to capture programmers’ reading behavior in an unobtrusive and precise way. Now the goal is to verify the described patterns by using eye tracking data from expert and novice programmers. In the experiment they have to detect errors in six different codes and take part in a retrospective interview. At the moment, data collections are ongoing. At the time of the conference, we will present the results of our analyses. Y1 - 2018 ER - TY - CHAP A1 - Hutzler, Ivonne A1 - Hauser, Florian A1 - Reuter, Rebecca A1 - Mottok, Jürgen A1 - Gruber, Hans T1 - Will the noun/verb analysis be used to generate class diagrams? An eye tracking study T2 - IATED, 11th International Conference of Education, Research and Innovation (ICERI 2018), 12-14 November 2018, Seville, Spain Y1 - 2018 U6 - https://doi.org/10.21125/iceri.2018.1103 SP - 505 EP - 514 ER - TY - CHAP A1 - Hauser, Florian A1 - Mottok, Jürgen A1 - Reuter, Rebecca A1 - Hutzler, Ivonne A1 - Gruber, Hans T1 - Eye movement patterns in software engineering – What differs the expert from the novice? T2 - IATED, 11th International Conference of Education, Research and Innovation (ICERI 2018), 12-14 November 2018, Seville, Spain Y1 - 2018 U6 - https://doi.org/10.21125/iceri.2018.1129 ER - TY - RPRT A1 - Hauser, Florian A1 - Mottok, Jürgen ED - Baier, Wolfgang T1 - Eye movement patterns im Software Engineering T2 - Forschung 2018 / Ostbayerische Technische Hochschule Regensburg Y1 - 2018 UR - https://doi.org/10.35096/othr/pub-1382 SP - 48 EP - 49 ER - TY - JOUR A1 - Gegenfurtner, Andreas A1 - Boucheix, Jean-Michel A1 - Gruber, Hans A1 - Hauser, Florian A1 - Lehtinen, Erno A1 - Lowe, Richard K. T1 - The gaze relational index as a measure of visual expertise JF - Journal of Expertise N2 - Eye tracking is a powerful technique that helps reveal how people process visual information. This paper discusses a novel metric for indicating expertise in visual information processing. Named the Gaze Relational Index (GRI), this metric is defined as the ratio of mean fixation duration to fixation count. Data from two eye-tracking studies of professional vision and visual expertise in using 3D dynamic medical visualizations are presented as cases to illustrate the suitability and additional benefits of the GRI. Calculated values of the GRI were higher for novices than for experts, and higher in non-representative, semi-familiar / unfamiliar task conditions than in domain-representative familiar tasks. These differences in GRI suggest that, compared to novices, experts engaged in more knowledge-driven, top-down processing that was characterized by quick, exploratory visual search. We discuss future research aiming to replicate the GRI in professional domains with complex visual stimuli and to identify the moderating role of cognitive ability on GRI estimates. KW - eye tracking KW - fixations KW - information processing KW - professional vision KW - visual expertise Y1 - 2020 UR - https://www.journalofexpertise.org/articles/volume3_issue1/JoE_3_1_Gegenfurtner.pdf SN - 2573-2773 VL - 3 IS - March SP - 32 EP - 40 PB - Michigan State University ER - TY - CHAP A1 - Hauser, Florian A1 - Mottok, Jürgen A1 - Gruber, Hans ED - Mottok, Jürgen T1 - Eye Tracking Metrics in Software Engineering T2 - Proceedings of the 3rd European Conference of Software Engineering Education (ECSEE'18); Seeon/ Bavaria Germany, 14.06.2018 -15.06.2018 N2 - This paper aims to provide an overview of the interdisciplinary combination of educational science, psychology, software engineering and the eye tracking methodology. The domain of software engineering is offering great potential for applied eye tracking research and in turn it can benefit from the possibilities of this upcoming technology as well. Nevertheless, software engineering has to struggle with some obstacles. These are namely the different terms, missing guidelines for experimental setups and a lack of common and standardized metrics. If eye tracking should be used in a broader way these problems must be solved. The main purpose of this paper is to list all eye tracking metrics which are relevant for software engineering and to give guidelines to help beginners by avoiding possible pitfalls. Y1 - 2018 SN - 9781450363839 U6 - https://doi.org/10.1145/3209087.3209092 SP - 39 EP - 44 PB - ACM CY - New York, NY ER - TY - CHAP A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Mottok, Jürgen T1 - Accessing the Presentation of Causal Graphs and an Application of Gestalt Principles with Eye Tracking T2 - 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER 2022), 1st Workshop on Advances in Human-Centric Experiments in Software Engineering (HUMAN 2022): 15-18 March 2022, Honolulu, HI, USA N2 - The discipline of causal inference uses so-called causal graphs to model cause and effect relations of random variables. As those graphs only encode a relation structure there is no hard rule concerning their alignment. The present paper presents a study with the aim of working out the optimal alignment of causal graphs with respect to comprehensibility and interestingness. In addition, the study examines whether the central gestalt principles of psychology apply for causal graphs. Data from 29 participants is acquired by triangulating eye tracking with a questionnaire. The results of the study suggest that causal graphs should be aligned downwards. Moreover, the gestalt principles proximity, similarity and closure are shown to hold true for causal graphs. KW - causal graphs KW - gestalt principles KW - eye tracking Y1 - 2022 U6 - https://doi.org/10.1109/SANER53432.2022.00153 SP - 1278 EP - 1285 PB - IEEE ER - TY - CHAP A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Mottok, Jürgen T1 - Evaluating Graph-based Modeling Languages T2 - Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - As humans, we tend to use models to describe reality. Modeling languages provide the formal frameworks for creating such models. Usually, the graphical design of individual model elements is based on subjective decisions; their suitability is determined at most by the prevalence of the modeling language. With other words: there is no objective way to compare different designs of model elements. The present paper addresses this issue: it introduces a systematic approach for evaluating the elements of graph-based modeling languages comprising 14 criteria – derived from standards, usability analyses, or the design theories ‘Physics of Notations’ and ‘Cognitive Dimensions of Notations’. The criteria come with measurement procedures and evaluation schemes based on reasoning, eye tracking, and questioning. The developed approach is demonstrated with a specific use case: three distinct sets of node elements for causal graphs are evaluated in an eye tracking study with 41 subjects. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593664 SP - 120 EP - 129 PB - ACM ER - TY - CHAP A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Mottok, Jürgen T1 - Something Short Gets Even Shorter: Adapting the LIST-K for the Use in an Online Learning Management System T2 - Proceedings of the 5th European Conference on Software Engineering Education, Seeon/Germany, June 19 - 21, 2023 N2 - This study examines how Klingsieck’s LIST-K questionnaire [22] can be shortened and adapted to the requirements of an online learning management system. In a study with 213 participants, the questionnaire is subjected to an exploitative factor analysis. In a next step, the results are evaluated in terms of their reliability. This process creates a modified factor structure for the LIST-K, comprising a total of eight factors. The reliability of the modified questionnaire is at an α of .770. The shortened version of the LIST-K questionnaire is currently being used on an experimental basis in different courses. Y1 - 2023 SN - 978-1-4503-9956-2 U6 - https://doi.org/10.1145/3593663.3593684 SP - 65 EP - 72 PB - ACM ER - TY - CHAP A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Mottok, Jürgen A1 - Gruber, Hans T1 - Visual Expertise in Code Reviews: Using Holistic Models of Image Perception to Analyze and Interpret Eye Movements T2 - ETRA '23: 2023 Symposium on Eye Tracking Research and Applications, Tubingen Germany 30 May 2023- 2 June 2023 N2 - This study uses holistic models of image perception to analyze and interpret eye movements during a code review. 23 participants (15 novices and 8 experts) take part in the experiment. The subjects’ task is to review six short code examples in C programming language and identify possible errors. During the experiment, their eye movements are recorded by an SMI 250 REDmobile. Additional data is collected through questionnaires and retrospective interviews. The results implicate that holistic models of image perception provide a suitable theoretical background for the analysis and interpretation of eye movements during code reviews. The assumptions of these models are particularly evident for expert programmers. Their approach can be divided into different phases with characteristic eye movement patterns. It is best described as switching between scans of the code example (global viewing) and the detailed examination of errors (focal viewing). Y1 - 2023 U6 - https://doi.org/10.1145/3588015.3589189 SP - 1 EP - 7 PB - ACM ER - TY - CHAP A1 - Röhrl, Simon A1 - Staufer, Susanne A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Bugert, Flemming A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Ezer, Timur A1 - Mottok, Jürgen T1 - PYTHIA - AI SUGGESTED INDIVIDUAL LEARNING PATHS FOR EVERY STUDENT T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - During the COVID-19 pandemic, the importance of digital course rooms, where teachers provide their learning materials, increased dramatically. While these platforms are crucial for providing teaching materials, they often fall short in addressing individual student needs. A system within an academic setting, capable of creating and presenting individual learning paths for each student, can solve these issues. These paths are composed of various learning elements - defined in our previous work as units of educational content with which a learner works. Currently, there is no suitable system that enables the integration of learning path generating algorithms into a digital course room. Therefore we present an application that enables this integration into the Moodle Learning Management System (LMS). More precisely, this paper presents a Moodle plugin together with its framework. It describes the mechanism for effectively collecting data from Moodle, which AI algorithms then use to generate personalized learning paths. Subsequently these paths are visualized with the help of the Moodle plugin. We started with a set of requirements and use cases for the interface connecting Moodle to the AI system, which were established with a group of experts. Based on the requirements, various relevant technologies were assessed, and the best ones were chosen for implementation. Following that, the paper develops a strategy for software structuring as well as an architecture, focusing on performance, modularity, and ease of deployment for widespread use. Furthermore, the architecture ensures a simple method for integrating the algorithms. Afterwards, the framework's concrete implementation is described. A technique for enriching learning elements with metadata is presented, and additionally a concept for presenting these learning elements within a hierarchy. Moreover, it is shown how questionnaire responses and learning analytics are utilized for data collection. We cover in detail techniques for extracting and storing data from the Moodle database, as well as methods for customizing Moodle course rooms and a standard API for incorporating AI algorithms. Finally, the paper discusses the application of the proposed framework in an actual course and how student feedback is collected, which could enhance the framework. It concludes with an assessment of the outcomes obtained and prospects for the framework's future advancements. KW - Personalized Learning Paths KW - Learning Management System KW - Software Architecture KW - Moodle KW - Artificial Intelligence Y1 - 2024 SN - 978-84-09-59215-9 U6 - https://doi.org/10.21125/inted.2024.0783 SN - 2340-1079 SP - 2871 EP - 2880 ER - TY - CHAP A1 - Staufer, Susanne A1 - Hauser, Florian A1 - Grabinger, Lisa A1 - Bittner, Dominik A1 - Nadimpalli, Vamsi Krishna A1 - Bugert, Flemming A1 - Ezer, Timur A1 - Röhrl, Simon A1 - Mottok, Jürgen T1 - Learning elements in LMS - a survey among students T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - In higher education, improving learning and learning success are goals of general improvement. Lecturers teaches content and students acquire that content in an efficient way. To structure content, learning element categories are evaluated from the student's point of view in higher education area. The aim is to validate given definitions of ten learning element categories within a Learning Management System (LMS). This paper evaluates a categorization of learning elements for organizing learning content in online education within LMSs. Therefore, ten categories of learning elements and corresponding definitions were defined in a previous work as base for this paper. The learning elements to examine are manuscript, exercise, quiz, brief overview, learning goal, summary, collaboration tool, auditory additional material, textual additional material, and visual additional material. To validate the definitions and to get improvements to each learning element a survey is processed. Beside the demographic data questions, the survey consists of two questions to the acceptance of the definitions and asks for improvements. 148 students between the ages 19 and 35 participate in the survey in summer term 2023. The education level of the participants ranges from undergraduates to Ph.D. students. The results of this paper are that more than 80% accept the given definitions. Some definitions of the learning elements are changed, but the changes are restricted to additions of maximal four words. This categorization of learning elements could lead to improvements in learning by giving the content more structure. With the structure students get the possibility to learn with preferred learning elements which could lead to more success in learning and to a decreasing dropout rate in universities. In the future, the learning elements allow to classify content within LMSs with the goal of generating individual learning paths. Furthermore, our project will integrate these learning elements, use them to generate learning paths, and could set a new standard in the way of personalized learning. KW - Learning elements KW - learning management system KW - learning objects KW - questionnaire KW - higher education area KW - content organization Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-71135 SN - 978-84-09-59215-9 SN - 2340-1079 SP - 4224 EP - 4231 PB - IATED ER - TY - CHAP A1 - Grabinger, Lisa A1 - Ezer, Timur A1 - Hauser, Florian A1 - Mottok, Jürgen T1 - The impact of eyenalyzer T2 - ICERI2024 Proceedings: 17th Annual International Conference of Education, Research and Innovation, 11th-13th November 2024, Seville, Spain N2 - Empirical research poses numerous challenges for beginners. This is especially true for data analysis – a task that usually requires knowledge from two distinct areas: statistics and programming. To support prospective researchers with that task, we developed a web-based tool called eyenalyzer. It supports common activities in the data analysis phase of empirical studies in a way that is suitable for novices in both, statistics and programming. The present article describes a controlled experiment investigating the impact of this tool with a total of 20 participants. All of them are given a set of common data analysis tasks. Half of the participants complete the tasks using eyenalyzer, the other half can use anything except for eyenalyzer. For each task and participant, we record the time in minutes, the task score, and the perceived difficulty. The results confirm that our tool is a valuable support for novice researchers: With eyenalyzer, the participants are significantly faster, achieve higher scores, and perceive the tasks to be less difficult. KW - tool evaluation KW - data analysis KW - eye tracking KW - empirical research Y1 - 2024 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:898-opus4-78215 SN - 978-84-09-63010-3 SN - 2340-1095 SP - 695 EP - 701 PB - IATED ER - TY - CHAP A1 - Ezer, Timur A1 - Grabinger, Lisa A1 - Hauser, Florian A1 - Staufer, Susanne A1 - Mottok, Jürgen T1 - EYE TRACKING AS TECHNOLOGY IN EDUCATION: FURTHER INVESTIGATION OF DATA QUALITY AND IMPROVEMENTS T2 - INTED2024 Proceedings: 18th International Technology, Education and Development Conference, Valencia, Spain. 4-6 March, 2024 N2 - Eye tracking serves as a powerful tool across a variety of empirical research areas: From usability research over cognitive research to educational research and applications in classrooms. However, data noise in eye tracking data poses a challenge to researchers and educators, as it leads to gaze positions being measured imprecisely under unfavorable conditions. In our previous study, we systematically investigated factors that influence data quality and are easily controllable in a classroom or laboratory environment, such as illumination, sampling frequency, and head orientation. However, no recommendations regarding the light source and light orientation could be provided, as these influences could not be analyzed in sufficient detail. Yet, a further examination of these factors, eliminating human influences by using an artificial head, revealed significant differences between individual settings. Hence, in this empirical study of eye tracking as an educational technology, we delve deeper into examining the impact of both light source and light orientation on data quality. This is investigated with an artificial head together with the Tobii Pro Spectrum eye tracking device. To measure data quality, we use the metrics precision and standard deviation as indicators of data noise. The obtained results derive practical advice for educators and researchers, such as not to illuminate the subject from the rear, in order to gather useful data for research and future classroom applications. Thereby, this study serves as a complement to our previous research, answering open questions regarding best practices for researchers and educators when using eye trackers. It aims to provide valuable insights into producing data of the highest quality possible when using eye trackers, both in laboratory settings and in future classrooms applications. KW - Eye tracking KW - data quality KW - best practices KW - lighting conditions KW - standard deviation KW - precision Y1 - 2024 SN - 978-84-09-59215-9 U6 - https://doi.org/10.21125/inted.2024.0802 SN - 2340-1079 SP - 2955 EP - 2961 PB - IATED Academy ER -