Background and Context. One goal of K-12 computing education is to teach computational concepts that support learners in responsibly and competently using and evaluating digital technologies. However, recent research indicates that students struggle to make use of such concepts in everyday life. Additionally, research shows that people develop powerlessness and resignation about data-driven technologies, leading to passive user roles. This raises the question of how to support students’ empowerment in navigating and shaping the digital world.

Worldwide, women are underrepresented in computer science. The differences between the numbers of male and female graduates from computer science programs are undeniable. This study examines how several previously reported factors of students' secondary school years relate to beginning CS students' intention to continue their studies. Among others, we investigated secondary school computer science education, role models, and extra-curricular activities and conducted a survey (N=424) in the first semester of CS in four universities from four different federal states of Germany. Our data shows that there is a significant relation between female students' intention to continue with their studies and their secondary school computer science education, with participating in an extra-curricular programming activity, and also negatively with the discouragement they had during their education - which is not the same for male or non-binary students. According to additional qualitative data, families play an essential role in both encouraging and discouraging predominantly female students in their continuity of computer science education.

School students interact with various data-driven applications in their everyday lives. Their motivations and intentions to engage with these technologies in everyday life from a computing perspective are rarely examined. However, this could inform the development of approaches to broadening participation and engagement in K-12 computing education. In this article, we present a questionnaire-based study of students' motivations and implementation intentions to engage with the data in data-driven technologies when interacting with them in everyday life. We surveyed 398 students between the ages of 12 and 16 and used structural equation modeling for analysis to examine students' motivations and intentions, as well as potential differences by gender and age. The study indicates that students have moderate motivations and intentions to engage with the CS-related aspects of data-driven technologies. The results suggest that older students are less curious about explanations for data-driven technologies than younger students, but gender does not play a significant role.

The disciplinary identity as a computer science student has recently received increasing attention as a well-developed subject identity can help with increasing retention, interest, and motivation. Besides, identity theory can serve as an analytical lens for issues around diversity. However, identity is also often perceived as a vague, overused concept with a variety of theories to build upon. In addition, connections to other topics, such as computer science conceptions, remain unclear and there seems to be little intra-disciplinary exchange about the concept. This article, therefore, attempts to provide a starting point by presenting a so far missing systematic literature review of identity in Computing Education Research (CER). We analyzed a corpus of 41 articles published since 2005 with a focus on the variety of identity theories that are used, the reasons for using them, and the overall theoretical framing of the concept in the CER literature up to this point. We use content analysis with both inductive and deductive coding to derive categories from the corpus to answer our research questions. The results show that there is less variety in the theories than originally expected, most publications refer to the theory of “Communities of Practice”. The reasons for employing identity theory are also rather canonical, in particular, there is only little theoretical development of the theories within CER and also only little empirical work. Finally, we also present an extended version of a computing identity that can be theoretically derived from the work in our corpus.

The identity or self-concept of computer scientists has received increasing attention in the computing education research (CER) literature in recent years. Identity is often considered relevant both for initially choosing a path of study and subsequent retention. It is therefore also considered highly relevant for the questions of how to reduce drop-out rates and broadening participation of currently underrepresented groups in computing in higher education. However, as more and more students have eligible or mandatory computing education in their K-12 years, identity may become relevant in this area as well.

A notional machine is a pedagogic device to assist the understanding of some aspect of programs or programming. It is typically used to support explaining a programming construct, or the user-understandable semantics of a program. For example, a variable is like a box with a label, and assignment copies or moves a value into that box. This working group will capture examples of notional machines from actual pedagogical practice, as expressed in textbooks (or other teaching materials) or used in the classroom. We will interview at least 30 teachers about their experience with, and perceptions of, the use of notional machines in teaching. Using the interviews, we will work on devising and refining a form to characterise essential features of notional machines. We will also attempt to relate them to each other to describe potential learning sequences or progressions. The working group report will contain descriptions of notional machines used at different levels in education, in different countries, by many teachers. Capturing and Characterising Notional Machines Sally Fincher, Johan Jeuring, Craig S Miller Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). ITiCSE 2020,,Trondheim, Norway © 2020 Copyright held by the owner/author(s). 978-1-4503-0000-0/18/06...$15.00 https://doi.org/10.1145/1234567890 The resulting catalogue of notional machines will allow a teacher to select a machine for a particular use, permit comparison between them, and provide a starting point for further categorization and analysis of notional machines. Additionally, we will make more theoretical explorations. We will explore a variety of presentational formats, examining what is necessary and what superfluous; we will look for dimensions of comparison and will examine how notional machines are instantiated across the discipline. We argue that the creation and use of notional machines is potentially a signature pedagogy for computing [1] and that creating and using notional machines represents a certain level of pedagogic sophistication that might be an indicator of pedagogic content knowledge (PCK).

We present, as a case study, the web-based platform Levumi that enables teachers to easily monitor learning \nprogressions of children with a focus on elementary skills in reading, writing, and mathematics. Curriculumbased \nmeasurements are used that can be administered economically in short time and - in many parts - in \nparallel for multiple children. The system is built around exchanging data between schools and educational \nresearch, such that data with high ecological validity can be collected anonymously in order to gain insights \ninto learning processes and in turn offer improved tests for teachers. For this case study, the acceptance and \nuse of the platform over the last years is evaluated with a focus on tests for reading abilities. The results show \nhow that many users are integrating the system in their daily teaching, learning progressions can be assessed \nand that the data is even usable for validation purposes.

Abstract Our paper introduces and assesses the Levumi platform’s web-based assessment of reading fluency. One challenges of inclusive education is meeting the needs of the learners with special education needs (SEN). Children with SEN and other risk factors face an increased risk of failing in schools and manifesting academic and social problems over the time. Web-based curriculum-based measurement (CBM) can provide an effective tool to track progress of learners and limit such risks. In particular, it can ease the challenges of test administration in inclusive classrooms through automation and providing multiple difficulty levels without the need of different paper-forms. Furthermore, Levumi can help educators track children and thus provide support for learners. Levumi takes advantage of the strengths of web-based CBM to assess reading fluency in primary school students. We confirmed the reading fluency test’s test-retest reliability (n = 334), its ability to measure learning over time in individual learners with SEN (n = 8, across 14 MPs), and its applicability to learners with SEN (n = 300, including n = 46 with SEN). We evaluate Levumi’s overall usefulness in assessing different types of learners, and discuss its contributions to CBM research.

Current CS1 learning outcomes are relatively general, specifying tasks such as designing, implementing, testing and debugging programs that use some fundamental programming constructs. These outcomes impact what we teach, our expectations, and our assessments. Although prior work has demonstrated the utility of single concept assessments, most assessments used in formal examinations combine numerous heterogeneous concepts, resulting in complex and difficult tasks.

ccording to the current state of research, it seems uncontroversial that the Pedagogical Content Knowledge (PCK) of teachers is a crucial factor for the success of teaching and learning in the context of many school subjects. Yet, the research about PCK in the subject of computer science (CS) is still sparse. Thus, we are working on a conceptualization of PCK for computer science (CS) that is based on literature on the one hand and empirically validated on the other. As a first step towards this goal, we have developed a category system from a set of publications from general pedagogy as well as from educational research in other subjects. Additionally, we have compared this system with the outcomes of a former survey among teachers about the preparation of lessons. Currently, we are coding all curricula for teacher education in Germany with this category system and preparing interviews among experts, applying the Critical Incident Technique.

In order to explore and validate suitable methods for investigating learning processes, we are currently conducting a case study, exploring the mental models of novice students in the field of object oriented modeling and programming. After abstracting and systemizing the information that was presented to the students of our introductory CS 1 course for non-majors we have asked them to draw concept maps at four points in time. Additionally, we conducted a small midterm exam, where the students had to implement some of the most important concepts and a regular final exam. We found that learning progress can be observed in detail by evaluating the concept maps.

We present first results of an ongoing research that investigates the learning progress of students in a CS course, using concept maps. We aim to indentify knowledge elements that are prerequisites for basic competencies in object oriented programming.

In the year 2004, Bavaria (one of the 16 federal states of Germany) started an innovative subject Informatics in its highest type of secondary schools (Gymnasiums). It is comprised of a compulsory stage (grades 6--10), which is followed by an eligible course in grades 11 and 12. The curriculum of the course is based on the objects (or better modelling first) approach. All relevant object-oriented concepts are introduced and used in the context of standard software, before the students write their first object--oriented program. In July 2009 the first class completed the compulsory stage. We evaluated the experiences of this first run in December 2009 by a large scale study about the teachers' opinions about and attitude towards this new subject. In this paper we present some of the first results that partly were obtained using cluster analysis. The results show, that our approach to the curriculum is accepted by the teachers. Additionally, we used the results of clustering to identify typical response patterns, leading to a characterization of the teachers.