External Doctoral Candidates

External Doctoral Candidates

M.Ed. Stephan Napierala

External Ph.D. Student

M.Ed. Stephan Napierala

Room:
SM-106
Telephone:
+49 201 18-34743
Fax:
+49 201 18-36897
Email:
Consultation Hour:
n.V.
Homepage:
https://www.ddi.wiwi.uni-due.de/team/externe-doktoranden/stephan-napierala/
Address:
University of Duisburg-Essen, Campus Essen
Faculty of Business Administration and Economics
Computer Science Education
Schützenbahn 70
45127 Essen

Curriculum Vitae:

Fields of Research:

  • Education in a digital world
  • Students interests

Projects:

  • INSDIG:Interests of Students in a Digital World

Publications:

Filter:
  • Napierala, S.; Brinda, T.: Student’s Rating of Contexts for Teaching Data Literacy at School regarding the Context Characteristics relation to everyday life and uniqueness. In: Acm (Ed.): Proceedings of the 20th Koli Calling International Conference on Computing Education Research (Koli Calling '20), November 19-22, 2020, Koli, Finland. ACM Press, New York, NY, USA 2020. doi:10.1145/3428029.3428037CitationDetails

    Preparing young people for their future with digital competenciesis an important goal for all educational systems. Competency frame-works already exist in many countries and function as guidelinesfor teaching at school. A central area is the data and information literacy, which also plays a key role in computing (education). As a school relevant topic it should therefore be examined more closely. For any learning activity, the interest in what to learn has a major impact on learning motivation and success. But the development of interests in school subject contents is also affected by its teaching contexts. In this respect, it is an open question whether these contexts should be related close to the everyday life of the students or whether they should be unique to have a positive effect on the situational interest of the students. Results can help selecting motivational teaching contexts and to facilitate the learning process, making it easier for students to acquire the required competencies. This paper presents results of a pilot study (N=28), which is part of a bigger research project consisting of two main studies. This pilot study belongs to the first main study. We present results on how 7th and 8th graders rated 12 contexts for teaching data literacy regarding the relation to their everyday life or uniqueness. This pilot study primarily serves to test a self developed questionnaire and its comprehensibility to use it in the first main study. It also gives first insights into expected results of the upcoming main study.

  • Napierala, S.: The Road to Finding Interesting Contexts for Teaching Data Literacy at School. In: Acm (Ed.): 15th Workshop in Primary and Secondary Computing Education (WiPSCE '20), October 28-30, 2020, Virtual Event, Germany. ACM Press, New York, NY, USA 2020. doi:10.1145/3421590.3421620CitationDetails

    Interest has a not negligible effect on learning motivation and success. Thereby, the development of interests in school subject contents is also affected by its context during teaching. Whether these contexts should be close to the everyday life of the students or more distant (uncommon) in order to be more interesting for them, is an open question.
    In this paper, a selection of 12 contexts for teaching data literacy is described and first findings are presented on how 7th and 8th grade students assess these contexts in relation to everyday life. This pilot study (N=28) primarily serves to test the questionnaire and its comprehensibility, but also gives first insights on expected results for the upcoming main study.

  • Napierala, S.: Why Not Ask Those Who Are Affected? - Development of an Instrument to Measure Students’ Interests. In: Acm (Ed.): 14th Workshop in Primary and Secondary Computing Education (WiPSCE’19), October 23–25, 2019, Glasgow, Scotland Uk. ACM Press, New York, NY, USA 2019. doi:10.1145/3361721.3362105CitationDetails

    Education for the so-called "digital world" is becoming more and
    more important these days and is given particular attention in
    school education. In this area, interdisciplinary educational fields,
    such as data literacy, have developed. However, on the one hand
    little is known about the interests of students in such educational
    topics and in the digital world itself but on the other hand interest
    is an important factor during the learning process. Therefore, in
    this poster abstract the literature-based development of an interest
    model for data literacy and a questionnaire based on this model
    are described with the aim to investigate students’ interests in this
    field.

  • Brinda, T.; Napierala, S.; Tobinski, D.; Diethelm, I.: Student Strategies for Categorizing IT-Related Terms. In: Education and Information Technologies, Vol 24 (2019) No 3, p. 2095-2125. doi:10.1007/s10639-019-09861-yFull textCitationDetails

    The ability to categorize concepts is an essential capability for human thinking and action. On the one hand, the investigation of such abilities is the purview of psychology; on the other hand, subject-specific educational research is also of interest, as a number of research works in the field of science education show. For computer science education, no corresponding studies are currently available. However, investigating how learners build categories from a choice of given terms may be useful for several reasons; for example, learners’ perspectives on relations between terms, as well as potential misconceptions, can be detected and made available to educators aiming to improve lesson planning. Therefore, we conducted an empirical study with 490 German students from primary to higher education, in which we presented them with 23 information technology-related terms (such as computer, Facebook, hard drive, virus) on a questionnaire, with the task of assigning these to self-defined categories (and then giving their categories individual names). In the results, we identified a number of potential categorization strategies the participants might have used to categorize the given terms; these include generalization, purpose, place of use, state, part-whole relationships, and association. Recognizing and defining such categorization strategies can help teachers construct learner-adequate concept maps of the domain, which helps foster the elaboration of learners’ knowledge structures in this field. We found that the younger participants used less abstract names for their categories, and observed that some participants had difficulty categorizing some terms (such as robot and 3D).

  • Brinda, T.; Napierala, S.; Behler, G.: What do Secondary School Students Associate with the Digital World?. In: Acm (Ed.): Proceedings of the 13th Workshop in Primary and Secondary Computing Education (WIPSCE 2018), Potsdam, Germany, 4.-6. Oktober 2018. ACM Press, New York 2018. doi:10.1145/3265757.3265763Full textCitationDetails

    Digitalization has progressed rapidly in recent years and will probably continue to do so in the future, which impacts all our everyday lives. Work life is changing and so is education. In 2006, the European Union dened digital competence as one of eight key competences for lifelong learning. As a result, a process of defining "education in the digital world” began, which is not yet completed. But what is the digital world anyway from the students’ points of view? In this paper, we present answers to this question given by 198 students, who were in grades 5, 8, 9, 10, 11 or 12 of German secondary schools. As part of an association test, we asked them for the terms they think of, when they hear the term "digital world" on the one hand, and the terms "digital world" and "computer science" on the other. Students often associated terms such as computer, cellphone and internet, but also programming, communication, and social networks, but could only partially relate their terms to computer science. Our results show that the age, gender, extend of computer science education received and the free time students spent on computer science topics inuenced the associations they gave. Furthermore, the results indicate, in which areas it might be worthwhile in follow-up studies to investigate learners’ interests.

  • Brinda, T.; Napierala, S.; Tobinski, D.; Diethelm, I.: What Do the Terms Computer, Internet, Robot, and CD Have in Common? An Empirical Study on Term Categorization With Students. In: Acm (Ed.): Proceedings of the 13th Workshop in Primary and Secondary Computing Education (WIPSCE 2018), Potsdam, Germany, 4.-6. Oktober 2018. ACM Press, New York 2018. doi:10.1145/3265757.3265771Full textCitationDetails

    The ability to categorize concepts is an essential capability for human thinking and action. On the one hand, the investigation of such abilities is the subject of psychology, on the other hand, subjectspecific educational research is also of interest, as e. g. a number of research works in the field of biology show. For computer science education, so far there have been no corresponding studies available. This paper reports on an empirical study in which around 500 German students from primary to higher education were presented with 23 IT-related terms (such as computer, Facebook, hard drive, virus) with a request to assign these to self-defined categories and to give the categories individual names. This paper gives a first insight into the categorization behavior.

Memberships: