90749 - Computing Education

Learning outcomes

The course aims to provide theoretical knowledge, techniques and tools helpful in teaching computer science. At the end of the course, the student is familiar with the main pedagogical and didactical approaches for teaching computer science at different school levels. Students can organise and teach computer science courses, compare and choose different methodologies to generate teaching materials, and evaluate learning.

Course contents

Basic previous knowledge of Computer Science and programming is important in order to follow the course effectively.

The general aims of this course include:

• knowledge of some historical, epistemological and ethical aspects of Computer Science as a scientific discipline, and of the reasons why it needs to be taught;

• understanding of pedagogical aspects and learning theories in the context of Computer Science Education;

• knowledge of several teaching approaches specific to the subject;

• knowledge of the main cognitive difficulties posed by learning Computer Science, with particular reference to programming, and of possible scaffolding strategies and techniques to overcome them;

• knowledge of specific software tools and physical computing devices to support the teaching of Computer Science;

• ability to formulate and manage learning paths consistent with national guidelines and curricula related to Computer Science in schools of all levels;

• ability to design teaching activities that are consistent with specific learning objectives, methodologies, materials and forms of formative assessment.

Module 1 Topics

• Computer Science as a science.

• Teaching technological aspects: computer architecture, operating systems, networks.

• Methodologies for Computer Science Education:

  • dramatization;

  • making/tinkering with physical computing tools.

• Software licences (free software vs. proprietary software): implications for education.

Module 2 Topics

• Big ideas for Computer Science Education.

• Learning paradigms and theories, with particular reference to constructivism and constructionism applied to Computer Science Education.

• Instructional design: learning goals, specific learning objectives expressed operationally, taxonomies, competences, teaching units and learning units.

• Formative assessment and assessment for learning: rubrics, feedback, self-assessment, peer assessment and tools for observing learning processes. Assessment of Computer Science learning.

• Top-down and bottom-up approaches in teaching Computer Science.

• "Coding", computational thinking and Computer Science.

• Teaching programming, algorithms and data structures.

• Educational implications of the choice of programming languages.

• Difficulties and misconceptions in learning programming.

• Methodologies and scaffolding techniques for Computer Science Education, including unplugged activities, code reading and comprehension, debugging code written by others, visualizing the state of the machine during program execution, and guided activities for modifying or completing programs.

• Computer Science in school textbooks and in international and Italian school curricula.

• AI education, teaching programming with generative AI, implications of AI for teaching, learning and assessment in Computer Science.

Readings/Bibliography

No textbook needs to be purchased.

Materials required for exam preparation

The slides, articles, chapters and other documents to be studied will be indicated during the course and made available electronically on the course wiki (https://csed-unibo.github.io/#!index.md ) and on Virtuale (https://virtuale.unibo.it/ ).

Reference material

M. Lodi (2020). Introducing Computational Thinking in K-12 Education: Historical, Epistemological, Pedagogical, Cognitive, and Affective Aspects. Doctoral thesis. http://amsdottorato.unibo.it/9188/1/Tesi_Dottorato_Lodi.pdf . Selected chapters will be assigned for study during the course.

Free materials for further study

The Hello World magazine (https://helloworld.raspberrypi.org/ ) from the Raspberry Pi Foundation offers useful content, both theoretical and practical, for Computer Science Education. In particular, the special editions Big Book of Computing Pedagogy (https://helloworld.raspberrypi.org/books/big_book_of_pedagogy ) and Big Book of Computing Content (https://helloworld.raspberrypi.org/books/big_book_of_computing_content ) may be used as free materials for further study.

Recommended texts for further study

• S. Grover. Computer Science in K-12: An A-To-Z Handbook on Teaching Programming. Edfinity, 2020.

• S. Sentance, E. Barendsen, N.R. Howard, C. Schulte. Computer Science Education: Perspectives on Teaching and Learning in School. Bloomsbury Academic, 2023, 2nd ed. Additional resources freely available for download: https://www.bloomsburyonlineresources.com/computer-science-education-2

• O. Hazzan, T. Lapidot, N. Ragonis. Guide to Teaching Computer Science: An Activity-Based Approach. Third Edition. Springer, 2020. Freely downloadable from the UniBO network: https://link.springer.com/book/10.1007/978-3-030-39360-1

• S. Fincher, A. Robins. The Cambridge Handbook of Computing Education Research. Cambridge University Press, 2019. Freely downloadable from the UniBO network: https://doi.org/10.1017/9781108654555

Teaching methods

Classes alternate moments of theoretical framing, guided discussion, exercises and activities involving active student participation. Individual and group activities, collaborative learning techniques, flipped classroom activities, unplugged activities and dramatizations, analysis of cases and teaching materials, code reading and discussion exercises, design of teaching activities, and peer feedback are planned.

Part of the course is devoted to experimenting with and discussing methodologies and tools for Computer Science Education, including the use of physical materials, physical computing devices, programming environments and visualization tools. The activities are aimed at connecting theoretical contents with the concrete design of learning paths, materials, activities and forms of formative assessment.

Given the type of activities and the teaching methods adopted, attendance of this course unit requires all students to have previously completed modules 1 and 2 of the training course on health and safety in study and work environments, in e-learning mode: https://elearning-sicurezza.unibo.it/ .

Assessment methods

Given the participatory and interactive nature of the classes, attendance is strongly recommended.

The final exam consists, on a mandatory basis, of designing an innovative teaching activity, and the related materials, for teaching Computer Science contents chosen by the student and agreed with the instructors.

No prior submission of the designed materials is required.

The exam consists exclusively of an oral examination, graded on a 30-point scale, lasting up to 60 minutes per candidate and divided into three parts of about 20 minutes each.

1. Presentation of the instructional design. The student presents the design of a teaching activity, indicatively lasting 1-3 hours, explicitly addressing the aspects listed at https://csed-unibo.github.io/#!pages/struttura_esame.md : topic, school track and class, placement within a teaching unit or learning unit, elements of innovation, references to ministerial documents, prerequisites, specific learning objectives expressed operationally, methodological approaches, resources, spaces, equipment, micro-planning and formative assessment methods

2. Simulation. The student simulates a significant part of the designed activity, taking on the role of the teacher and addressing the school audience indicated in the design

3. Discussion. The student answers questions on the design, the simulation, the chosen Computer Science contents and the related Computer Science Education topics.

During the course, questionnaires and ongoing exercises will also be proposed to support the progressive consolidation of knowledge and skills. Assessment also takes into account in-class participation and the submission of any ongoing activities: submitting all activities on time and with a sufficient result entitles the student to one additional point.

The grading criteria are described in the rubric available at https://csed-unibo.github.io/#!pages/rubric_esame.md . Assessment considers the following dimensions: knowledge of Computer Science contents; conceptual correctness of Computer Science contents; Computer Science Education contents; innovativeness; consistency with school age and/or track; terminology; adequacy of the material with respect to learning goals and objectives; teaching methodologies; teacher guide; assessment; replicability; attention to students with difficulties and to particularly advanced students; simulation; ability to respond to the instructors' prompts.

If the student reaches, for all criteria, a "partial" level, they receive 18/30. If the student reaches, for all criteria, an "adequate" level, they receive 28/30. Higher grades are awarded when the proposal shows particular originality, is built or adapted on the basis of an extensive and justified search for existing materials, arouses curiosity about related Computer Science concepts, uses terms and examples that are fully appropriate for the audience and attentive to cultural and gender diversity, applies methodologies grounded in Computer Science Education research, proposes effective formative and continuous assessment methods, and, in the simulation, is engaging, responsive to prompts and well justified from an educational point of view.

Regarding the instructional design and exam materials, the use of generative AI is neither forbidden nor mandatory. It may be used as support for instructional design, for example to explore ideas, retrieve or reorganize information, compare alternatives, rephrase texts or produce drafts to be critically revised. During the oral presentation of the project, students must nevertheless demonstrate full command of the Computer Science contents and of the Computer Science Education contents cited, and must be able to justify pedagogically the design, methodological, assessment and material choices presented.

Students may accept or refuse the oral exam grade. Refusal of the grade will also be recorded on AlmaEsami. If students do not pass the oral exam or refuse the grade, they must attend one of the subsequent exam sessions with a design on a significantly different topic.

Students must attend the course in the academic year, 1st or 2nd, that matches the one indicated for this course unit in their study plan; in particular, it is not possible to attend the course in the 1st year if it is listed in the 2nd year.

Six exam sessions will be scheduled for each academic year: three in June/July, one in September, and two in January/February. Exams will not be offered by appointment.

Students with specific learning disorders or temporary or permanent disabilities are recommended to contact the relevant University office in good time (https://site.unibo.it/studenti-con-disabilita-e-dsa/en ); that office will propose any accommodations to the students concerned. These accommodations must in any case be submitted, 15 days in advance, for approval by the instructor, who will assess their appropriateness also in relation to the learning outcomes of the course unit.

Teaching tools

Classes will use slides, materials published on the course wiki and on Virtuale, programming environments, visualization tools, stationery, everyday objects and electronic boards or other physical computing devices useful for teaching Computer Science.

All materials will be published on the course wiki (https://csed-unibo.github.io/ ) and on Virtuale (https://virtuale.unibo.it/ ).

During class, students will be able to send messages to ask anonymous questions and respond to anonymous surveys.

What is projected in the classroom, without audio, is made available live on the web for students' convenience, for instance to follow the projection more easily or take a screenshot.

Office hours

See the website of Renzo Davoli

See the website of Michael Lodi