Andreas Mühling

Towards a conceptualization of pedagogical content knowledge for computer science

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.

Fast lowest common ancestor computations in dags

This work studies lowest common ancestor computations in directed acyclic graphs. We present fast algorithms for solving the ALL-PAIRS REPRESENTATIVE LCA and ALL-PAIRS ALL LCA problems with expected running time of O(n2 log n) and O(n3 log log n) respectively, where the expectation is taken over a distribution of input graphs. The speed-ups over recently developed methods are achieved by applying transitive reduction on the input dags. The algorithms are experimentally evaluated against previous approaches demonstrating a significant improvement. On the purely theoretical side, we improve the upper bound for ALL-PAIRS ALL LCA to O(n3.3399). We give first fully dynamic algorithms for both ALL-PAIRS REPRESENTATIVE LCA and ALL-PAIRS ALL LCA. Here, the non-trivial update complexities are O(n2.5) and O(n3) respectively, with constant query times.

Playing PISA with bebras

To test and adopt the methodology of future PISA surveys in Computer Science, we have utilized the Bebras Contest as a test field. We performed latent trait analysis of the questions of the German Bebras contest 2009 to find sets of questions that might measure joint psychometric constructs (competencies). After having identified several sets, we have tested the fit of the mono-parametric Rasch Model and evaluated the distribution of person parameters.

What students (should) know about object oriented programming

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.

Gender differences in programming: research results and teachers' perception

Women are severely underrepresented in the field of computer science. Already in school gender differences in CS, especially in programming, are observable. To face this, we surveyed 63 computer science teachers on their experiences regarding these differences between female and male students. The results of the survey were matched with findings from recent literature. We identified that teachers have only a limited perspective on the influences of gender on programming. Based on this results we are planning an intervention for computer science teachers.

Dimensions of Programming Knowledge

Nowadays, learning and teaching outcomes are defined predominantly by target competencies. In order to assess learning outcomes, properly defined and empirically validated competency models are required. For object-oriented programming, such models have not been brought forward up to now. Aiming to develop a competency structure and level model for this field, we have examined the structural knowledge of programming novices to derive its potential dimensions. The results suggest 6 dimensions. Additionally, we propose difficulty levels for two of these dimensions based on the SOLO taxonomy. The empirical validation of these dimensions and their levels is subject to further investigations.

Handling Heterogeneity in Programming Courses for Freshmen

One of the biggest challenges of the computer science department at our university is handling the enormous heterogeneity of freshmen concerning both their previous programming abilities and their learning behaviors due to their biographical and social background. In this paper, we present the design and evaluation of a preliminary programming course based on the teaching method of Mastery Learning that is particularly suited for groups of students characterized by considerable diversity. Trained peer tutors closely guide the participants through a step-by-step programming exercise. We tested the method in several courses that ran for two and a half days four weeks before the start of lectures. We collected data from two different surveys(N = 200 and N = 300, respectively). First, we quantified the considerable differences concerning the prior experience in programming of the participants. Second, we succeeded to show that the outcome of our method is independent from different sensory preferences and different computer-usage behaviors of the students. Third, the results of the survey demonstrate that our method is suited to increasing the self-perception of programming ability. This helps freshmen to overcome initial self-doubts when beginning their CS studies.

Competency Mining in Large Data Sets

In preparation of large scale surveys on computer science competencies, we are developing proper competency models and evaluation methodologies, aiming to define competencies by sets of exiting questions that are testing congruent abilities. For this purpose, we have to look for sets of test questions that are measuring joint psychometric constructs (competencies) according to the responses of the test persons. We have developed a methodology for this goal by applying latent trait analysis on all combinations of questions of a certain test. After identifying suitable sets of questions, we test the fit of the mono-parametric Rasch Model and evaluate the distribution of person parameters. As a test bed for first feasibility studies, we have utilized the large scale Bebras Contest in Germany 2009. The results show that this methodology works and might result one day in a set of empirically founded competencies in the field of Computational Thinking.

Investigating cognitive structures of object oriented programming

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.

How Learning Styles in CS Can Foster Inclusion of Visually Impaired Students

We present the results of a study of learning types of CS students. In computer science education there seems to be a prevalence of visually oriented teaching methods. However, as the results of our investigation show, the learners may not actually benefit from this trend. This is valuable information in the context of including visually impaired learners in computer science classes - since these learners suffers the greatest disadvantages from visually oriented teaching and learning aids. Our results indicate that a different approach to CSEd placing more emphasis on kinesthetic and textual material may be of advantage for all CS students alike and also foster the inclusion of visually impaired learners.