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How to Implement Rigorous Computer Science Education in K-12 Schools? Some Answers and Many Questions ¨ Munchen, ¨ PETER HUBWIESER, Technische Universitat Germany MICHAL ARMONI, Weizmann Institute of Science, Israel MICHAIL N. GIANNAKOS, Norwegian University of Science and Technology, Norway
Aiming to collect various concepts, approaches, and strategies for improving computer science education in K-12 schools, we edited this second special issue of the ACM TOCE journal. Our intention was to collect a set of case studies from different countries that would describe all relevant aspects of specific implementations of Computer Science Education in K-12 schools. By this, we want to deliver well-founded arguments and rich material to the critical discussion about the state and the goals of K-12 computer science education, and also provide visions for the future of this research area. In this editorial, we explain our intention and report some details about the genesis of these special issues. Following, we give a short summary of the Darmstadt Model, which was suggested to serve as a structuring principle of the case studies. The next part of the editorial presents a short description of the five extended case studies from India, Korea, NRW/Germany, Finland, and USA that are selected to be included in this second issue. In order to give some perspectives for the future, we propose a set of open research questions of the field, partly derived from the Darmstadt Model, partly stimulated by a look on large-scale investigations like PISA. Categories and Subject Descriptors: K.3.2 [Computer and Information Science Education]: Computer Science Education General Terms: Human Factors Additional Key Words and Phrases: Schools, curricula, CS education, K-12 education, research questions, Darmstadt Model ACM Reference Format: Peter Hubwieser, Michal Armoni, and Michail N. Giannakos. 2015. How to implement rigorous computer science education in k-12 schools? Some answers and many questions. ACM Trans. Comput. Educ. 15, 2, Article 5 (April 2015), 12 pages. DOI: http://dx.doi.org/10.1145/2729983
1. INTRODUCTION
After the appearance of the first special issue on Computer Science Education (CSE) in K-12 schools (K-12-CSE) in June 2014 [McCartney et al. 2014], we are happy to present the second special issue of TOCE on this topic. As our work on these special issues has now come to an end, it seems appropriate to reflect on the whole production process and provide some prospects for the future. First of all, we want to summarize the intentions and outcomes of our work on K12-CSE up to now. As described in detail in our editorial of the first issue [Hubwieser ¨ Munchen, ¨ Authors’ addresses: P. Hubwieser, Technische Universitat TUM School of Education, Arcisstrasse ¨ 21, 80333 Munchen, Germany; email:
[email protected]; M. Armoni, Department of Science Teaching, Weizmann Institute of Science, 76100 Rehovot, Israel; email:
[email protected]; M. N. Giannakos, Faculty of Information Technology, Mathematics and Electrical Engineering, NTNU, NO-7491 Trondheim NORWAY; email:
[email protected]. 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 show this notice on the first page or initial screen of a display along with the full citation. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, to redistribute to lists, or to use any component of this work in other works requires prior specific permission and/or a fee. Permissions may be requested from Publications Dept., ACM, Inc., 2 Penn Plaza, Suite 701, New York, NY 10121-0701 USA, fax +1 (212) 869-0481, or
[email protected]. c 2015 ACM 1946-6226/2015/04-ART5 $15.00 DOI: http://dx.doi.org/10.1145/2729983
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Fig. 1. The Darmstadt Model.
et al. 2014], we met each other in the working group “Computer Science/Informatics in Secondary Education” at the ITiCSE 2011 in Darmstadt, Germany. The original goal of this group was to collect, evaluate, integrate, and present research findings about Informatics/Computer Science (CS) in secondary schools. During the work in this group, we realized that the situation and the perspectives of K-12-CSE were very different and very context specific over the respective countries or states. Thus, aiming to provide a framework for the comparison and integration of concepts, experiences, and research outcomes on the field of K-12-CSE, we decided to develop a specific category system for this purpose. The outcome of the working group was a three-dimensional model, which was called the Darmstadt Model (DM) in honor of the location of the conference. The genesis and structure of the model was described in detail in the ITiCSE working group report [Hubwieser et al. 2011]. In the keynote speech of the ISSEP 2013, some slight changes were suggested by the associate editor of these special issues [Hubwieser 2013], which resulted in the current structure of the DM that is displayed in Figure 1. The complete model is listed in Table II in the Appendix. In consideration of the fact that most available publications about K-12-CSE were quite short, we proposed a special issue about K-12-CSE to the editors-in-chief of this journal. The goal should be to collect concepts, approaches, or strategies to improve the regular CSE in schools. In order to provide a leading example for these contributions, an extensive case study of the situation of K-12-CSE in Bavaria was published by the associate editor of the special issues [Hubwieser 2012]. After the first submission steps, it turned out that we would receive numerous high-quality articles. This justified a second special issue, which has finally appeared now. More details about the history of the two special issues can be found in the editorial of the first issue [Hubwieser et al. 2014]. Naturally, this editorial intends to provide a short overview of the articles that are published in this issue. Three of these articles provide rich information about the situation and perspectives of K-12-CSE in India, Korea, and in North-Rhine Westphalia, ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
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which is the largest of all 16 federal states of Germany. As some countries or states have serious reservations regarding the integration of CSE in their curricula, we have included two articles in this issue that describe extracurricular projects. We hope that these projects could serve as examples of how CSE could be delivered outside regular school education. Finally, we propose several research questions that are based on the experiences we have made during the work on this issue. For this, the DM turned out to be quite helpful once again. 2. RELATED WORK
As already mentioned in the editorial of the first issue, numerous research initiatives in the field of K-12-CSE are currently under way. As most of these initiatives are very multifaceted and comprehensive, it seemed infeasible to provide an exhaustive survey or metastudy of all these efforts here. Thus, we decided to refrain from any summary of this related work. Nevertheless, we suggest any interested reader to have an eye on the following publications. In 2012, the British Royal Society (BRS) published its groundbreaking report Shutdown or Restart [The Royal Society 2012]. This report raised important issues on K12-CSE, caused significant political awareness, and most importantly, led to initiatives of reintroducing Computing in schools with rigorous contents of Computer Science. The Computer Science Teachers Association (CSTA) of the ACM is one of the most active stakeholders of K-12-CSE. Besides its curricula, it has published two flagship articles about the state of K-12-CSE in the USA. The report The New Educational Imperative [Stephenson et al. 2005] provides a comprehensive look at high school CSE in the USA and around the world. The well-known study Running on Empty [Wilson et al. 2010] summarizes the state of K-12-CSE in the USA by examining and mapping current learning standards in core subject areas. The study revealed that roughly two-thirds of the country has CSE standards for secondary education, with few and scattered courses dedicated to CSE. Some months after our ITiCSE working group (mentioned previously), another working group gathered at the Koli conference in November 2011, aiming to investigate the international situation of K-12-CSE. The group conducted a survey among experts that reflected on their national state of CSE in schools and of CS teacher education [Schulte et al. 2012]. In 2013, a joint working group from Informatics Europe and ACM Europe, consisted of experts from academia and industry, published its report Informatics Education: Europe Cannot Afford to Miss the Boat [Informatics Europe and ACM 2013]. The report claims to “build on the considerable body of educational research and experimentation on digital literacy and informatics education developed over the past decades in Europe, the US and elsewhere.” It summarizes the situation of K-12-CSE in several countries and gives some comprehensive recommendations. 3. THE ARTICLES IN THIS SPECIAL ISSUE
To provide an overview, Table I in the Appendix displays all articles that have appeared in both special issues about K-12-CSE. A short summary of the Articles 1–1 to 1–8 of the first issue can be found in its editorial E1 [Hubwieser et al. 2014], while the Articles 2–1 to 2–5 of the second issue are summarized in the following. 3.1. India
The article “Computer Science (CS) Education in Indian schools: Situation Analysis using Darmstadt Model” by Raman, Venkatasubramanian, Achuthan, and Nedungadi, categorizes the state of CSE in India through the lens of the DM, and the Theory of Perceived Attributes. ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
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In particular, Raman et al. coded and analyzed the CS status of Indian schools. In addition, by emphasizing the motivation category of the DM, they investigated the behavioral intentions of secondary school students and teachers from 332 Indian schools. Looking at the CS subject as an educational innovation, Raman et al. used the Theory of Perceived Attributes to propose certain characteristics of CSE that significantly predict successful adoption of CSE by teachers and students. Based on data collected from 10,292 students and 996 teachers from 332 schools, useful insights regarding student and teacher intentions, influence of gender, school management, and school location in adopting CS were revealed. Interestingly, women, urban students, teachers, and private schools were seen favoring the adoption of CS in K-12 schools. In accordance with many other countries, in India there is also a confusion regarding the name and nature of the subject called “Computer Science” in K-12 education, since terms like CS, Informatics, ICT, and digital literacy are used interchangeably—without any difference in their actual meaning. 3.2. Korea
Korea is represented by the interesting case study “Computing Education in Korea— Current Issues and Endeavors,” by Choi, An, and Lee. As an elective subject (and similar to the situation in North-Rhine Westphalia; see next), the Korean school subject of CS currently suffers from very low selection ratio, the result of a very significant decrease occurring in the last 10 years. This is the case in spite (or maybe because) of the revised nature of this subject as a scientific one, emphasizing problem solving rather than digital literacy. This article examines the roots of this situation and future ways for remedying it. 3.3. North-Rhine Westphalia, Germany
The article “Computer Science Education in North-Rhine Westphalia, Germany—A Case Study,” by Knobelsdorf and her colleagues, presents the history and current situation of CSE in North-Rhine Westphalia, Germany’s most populated state. In this state, CS has been taught in high schools as an elective subject since the 1970s. This study again illuminates important issues with which we are already familiar from other case studies included in the two special issues. Among these issues, there are tensions between the perceived nature of the subject (and hence, the discipline itself) as a scientific science or as a subject of digital literacy, and the issue of CS as a mandatory or elective study. In addition, this case study depicts the CSE research community of North-Rhine Westphalia as a very distributed, active, and involved research community, and thus demonstrates the importance of the research component as an influential vehicle in the process of improving K-12 CSE. 3.4. MOOCs, Finland
The article “A Purposeful MOOC to Alleviate Insufficient CS Education in Finnish Schools” by Kurhila and Vihavainen, describes an initiative of the Department of Computer Science at the University of Helsinki. It developed a MOOC based on an introductory programming course (equivalent to CS1) and offered this course to all Finnish high schools. This initiative is particularly important, since the Finnish national school curriculum does not include any topics related to CS. To remedy this deficit, many schools in Finland have offered this online programming course as an elective CS course, and granted formal school credits for completing it. After two semesters of operation, the following results emerged: —Many school students in Finland are ready and willing to work on a challenging programming course online. ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
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—Bridging this programming course to a full study right makes a strong incentive to keep working on the programming assignments, even without traditional teaching. Interestingly, based on the collected data, school students who participated in the programming course (ages 15–19) did not consider the programming assignments to be more difficult compared to students over the age of 20, and showed similar progress throughout the course. The empirical findings of this study provide strong evidence that Finnish students are eager and competent to welcome CS subjects to their national school curriculum. 3.5. Scalable Game Design, USA
The article “Scalable Game Design: A Strategy to Bring Computer Science Education to Schools through Game Design and Simulation Creation” by Repenning et al., presents a strategy under the name Scalable Game Design (SGD), to integrate CSE into the regular school curriculum. At present, throughout K-12 education, there are few opportunities for young students to be exposed to computer programming. SGD was designed and conducted aiming at providing this exposure and improving K-12-CSE. In particular, SGD includes opportunities for students to design and program games and simulations according to the mission statement of the SGD: “Reinvent computer science in public schools by motivating and educating all students including women and underrepresented communities to learn about CS through game design starting at the middle school level.” After applying the SGD approach to more than 10,000 students, the “Computational Thinking Pattern Analysis” was employed to measure and analyze computational thinking skills. The SGD approach has demonstrated rapid adoption by teachers from multiple disciplines, high student motivation, high levels of participation by women, and interest regardless of demographic background. 4. FUTURE WORK AND OPEN RESEARCH QUESTIONS 4.1. The Big Questions of CSE
During the work on these special issues, it turned out that there are some research questions that are relevant in many different contexts, cases, and countries, among which, in our eyes, the most important ones are the following. —At what age should CS start? Which content, learning objectives, methods, and media are suitable to learn CSE concepts in primary schools? Does it pay off to give CSE teaching time in primary schools, taking this time away from other important learning fields? —What is CSE good for? Which superordinate competencies that are regarded as necessary and valuable by the majority of the society are supported by CSE? And which parts of CSE do really support these competencies, and in which respect? —How and when should programming be learned in K-12 schools? Which contributions to general education could be provided by learning to program? Which programming languages and which didactical approaches are the most suitable for the different age groups and school contexts? Beneath these apparently dominating questions, there is a mass of other open questions that are quite relevant altogether. In order to provide some structure for these, we propose to apply the DM once again. 4.2. Research Questions According to the DM
Unfortunately, although strongly suggested in the solicitation letter and our feedback on the draft submissions, the authors of the contributions of these special issues did ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
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not consider the categories of the DM (see Figure 1 and Appendix) as close as we had hoped. Nevertheless, the DM can be used now to analyze and compare all articles by qualitative text analysis. Yet, due to the depth of the papers, this will be a difficult and challenging task. Additionally, the DM can be used to generate research questions. By checking all categories of the dimension of educational relevant areas and all their combinations, ideas for research could be stimulated. The following list shows some questions that we find particularly relevant and interesting. When more than one educational relevant area of the DM is concerned, their numbers are indicated in parentheses. (1) Educational System: Organizational Aspects of Subject, Enrollment, School type —Which organizational forms are positively influential? —How should the subject of CS be integrated in the timetables? —Which factors influence enrollment? (2) Socioultural-Related Factors: History of ICT and Informatics in Schools, Age, Gender, Social and Immigration Background, Family Socialization, Public Opinion, Technoeconomic Development —How does the history of ICT, Informatics, or CS in schools influence the success of current policies? —How does gender and ethnic background influence CSE-related learning processes? How does motivation (5) and self-efficacy depend on gender? In particular, how to motivate girls to program? —How to integrate students with disabilities? In particular, how can blind students get access to learning content that is predominantly presented visually up to now (e.g., UML diagrams)? —Which abstraction levels (7) are suitable for the different age groups (e.g., abstract data types in lower secondary schools)? (3) Policies: Research and Funding Policies, Education Policies, Quality Management —Which policies or strategies turned out to be successful, under which circumstances, and in which educational systems (1)? (4) Teacher Qualification: Teacher Education, Professional Experience —Which level of preservice Teacher Education is necessary (e.g., Bachelor or Master degree in CS)? Is pure in-service training feasible? —How can Professional Experience be utilized? (5) Motivation: Student, Teacher —How to motivate all students, respecting their differences in age, gender, ethnic background, or disabilities? (2) —How to support and maintain teachers’ motivation (4)? (6) Intentions: Learning Objectives, Competencies, Standards —Which overall goals can be achieved by suitable CSE in the respective educational context (e.g., recruitment for CS courses at university, contributions to general education, self-reliability, self-responsibility, efficient user skills, or media competency)? (1) —Which taxonomies are suitable to assess the difficulty of learning objectives in CSE? —Which competencies can be measured (empirically) in CS, particularly regarding programming? How can they be defined? How do they develop during learning processes? —How should appropriate standards for CSE be defined? Which standards should be set for which level of K-12-CSE? (1) ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
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(7) Knowledge: CS, ICT —Which learning content is appropriate for K-12-CSE at which age level, and under which circumstances? (1) —How to integrate or relate to ICT skills or media literacy in rigorous CSE? (8) Curriculum Issues —How should CS school curricula be designed? —Which structure should CS school curricula have? —How detailed should CS school curricula be? —Who should be involved in the design process of CS school curricula? (9) Examination/Certification —How should CS competencies be measured? How should CS tests be designed? (6) —Which examination and certification types are suitable regarding the intended goals (6) and the specific educational context (1) (e.g., oral, written, portfolios)? (10) Teaching Methods: CSE, General Education —Which teaching methods were found to support the achievement of the specific learning objectives (6) in the respective educational context (1)? —Which goals can be achieved by applying programming as a learning method? (6) (11) Extracurricular Activities: Contest —Can extracurricular activities, for instance contests, MOOCs, or programming camps support CSE or even substitute for curricular deficits? Are certain extracurricular activities (e.g., contests, MOOCs, or programming camps) in accordance and attuned to the specific CS curriculum and its goals in the specific educational context? (1), (6), (8) —Which personal factors (intelligence facets, knowledge, or competencies) determine success in a CS contest? (2) —Is a contest motivating for students that are likely to succeed in CS? (5) (12) Media: Technical Infrastructure, Textbooks, Tools, Didactical Software, Visualization Software, Unplugged Media, Haptic Media —Which media (e.g., books, hard- or software systems, programming languages or environments, personal learning environments) were found to support motivation (5), learning objectives (6), competencies or learning content (7), and for which target group? (13) Outcomes/Effects —How can the outcomes of CSE be measured (assessed)? —What are the outcomes of a certain implementation of CSE (with specific manifestations of the preceding educational relevant areas 1–12)? Regarding the last question, in this context it might be necessary to measure and compare learning outcomes on the level of states or countries. Obviously, such measurement would require a methodology that is suitable for large-scale surveys. In consequence, one would have to look for already-working and proven methodologies for this level. At least in Europe, presumably the best-known and best-worked out largescale studies are the PISA studies, initiated and controlled by the Organisation for Economic Cooperation and Development (OECD) (see www.oecd.org/pisa). So far, the focus of PISA has been on mathematics, natural science, and language understanding. Yet, in our opinion, a PISA survey of CS competencies would advance the research methodologies of CSE in a pioneering way and might finally elevate this field to the level of educational research in traditional school subjects. We will elaborate on this in the next section. ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
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4.3. CSE and PISA
Since 2000, the OECD is conducting the well-known international PISA studies (Programme for International Student Assessment). Most member states of the OECD and a growing number of partner countries are participating in those studies in three-year cycles. While some of its political interpretations are heavily under discussion, the scientific community had to acknowledge that all PISA studies follow a sophisticated, well-founded methodology [Seidel and Prenzel 2008], which had a groundbreaking impact on the whole field of empirical educational research, at least in the participating school subjects. Yet, in order to be ready for PISA, research in CSE would have to carry out considerable prerequisite work. First, we have to find a normative grounding, that is, a set of abilities that are commonly accepted as educational goals, answering leading questions like “What is the contribution that CSE could deliver to help students have a successful, self-determined and responsible life in a modern society?” Potentially, some ideas could be taken from the concept of Computational Thinking (CT) [Wing 2006]. Second, as explained in Seidel and Prenzel [2008], the PISA questions are thoroughly designed to measure certain well-defined competencies, embedded in an empirically derived competency model. Thus, we need such a properly defined competency model, based on a normative grounding as CT, which would provide a framework for all measurements [Seidel and Prenzel 2008]. Despite some recent achievements (e.g., the MoKoM competency model [Magenheim et al. 2010]), this will require substantial research efforts and thus will take some years. Third, as Klieme et al. [2004] stress, measuring competencies is not an easy matter: “Competencies cannot be reflected by or assessed in terms of a single, isolated performance. Rather, the range of situations in which a specific competence takes effect always spans a certain spectrum of performance. Narrow assessments cannot meet the requirements of competency models. The seven facets of competence listed above make it quite clear that competence must be assessed by an array of tasks and tests that do more than simply tap factual knowledge.” In consequence, we have to develop test items, collected in booklets, based on our competency model. These items would have to be thoroughly validated to make sure that they are really measuring the intended competencies. Finally, we need to test and adopt the methodology of large-scale investigations to fit the context of CSE. For this purpose, the methodology of Item Response Theory [Rost and Carstensen 2002] has to be tested and validated in a sufficiently large scale. In summary, this might stimulate research regarding the following additional research questions: —Which theory could represent a suitable normative starting point for large-scale investigations? More precisely, what competencies in the field of CS should be learned by K-12 students? —How could a suitable framework be constructed? What would the competency structure model and the competency level model look like? We would need a structure model for tests based on multifactorial item response models. —How could a test of these competencies be constructed? Which items and contexts are suitable? How can the items be validated? —How should the setting of the tests be designed? Which influence factors could distort the measurements? 5. CONCLUSION
As already explained previously and in the editorial of the first special issue [Hubwieser et al. 2014], research projects that intend to provide answers to one or more of the ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
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research questions raised in Section 4, have to take into account the substantial differences in the contexts of CSE across countries, states, or even individual schools. To describe and differentiate theses contexts, we have developed the DM, enabling researchers to specify the relevant context of their studies to conduct an in-depth investigation and identify the challenges that need to be tackled. For instance, a researcher can focus on studying the decision areas at the school level of responsibility regarding the media. Obviously, the DM can be applied in a qualitative, quantitative, or even mixed research approach; the latter we see as being particularly important for the field of CSE. In summary, we are confident that these two special issues have made a substantial contribution to the field of CSE in K-12 schools, by bringing some active and engaged people together, by collecting a corpus of rich data from several extensive case studies about the situation of CSE in different countries around the world, and by stimulating further research about CSE at the K-12 levels. APPENDIX Table I. All Articles in the Special Issues No. 1st Issue
(Country) Authors Names
E1-1
Tenenberg, McCartney
E1-2
Hubwieser, Armoni, Giannakos, Mittermeir
1-1
(USA, Israel) Gal-Ezer, Stephenson
1-2
(UK) Brown, Sentance, Crick, Humphreys
1-3
(NZ) Bell, Andreae, Robins
1-4
(France) Baron, Drot-Delange, Grandbastien, Tort (Sweden) Rolandsson, Skogh (USA/Georgia) Guzdial, Ericson, McKlin, Engelman
1-5 1-6
1-7
(Russia) Khenner, Semakin
1-8
(Italy) Bellettini, Lonati, Malchiodi, Monga, Morpurgo, Torelli, Zecca
Title Trans. Comput. Educ., vol. 14, no. 2, June 2014 Editorial: Computing Education in (K-12) Schools from a Cross-National Perspective Perspectives and Visions of Computer Science Education in Primary and Secondary (K-12) Schools A Tale of Two Countries: Successes and Challenges in K-12 Computer Science Education in Israel and the United States Restart: The Resurgence of Computer Science in UK Schools A Case Study of the Introduction of Computer Science in NZ schools Informatics Education in French Secondary Schools. Historical and Didactical Perspectives Programming in School: Look Back to Move Forward Georgia Computes! An Intervention in a US State, with Formal and Informal Education in a Policy Context School Subject Informatics (Computer Science) in Russia: Educational Relevant Areas Informatics Education in Italian Secondary School
Type
Editorial of editors-in-chief Editorial of associate and guest editors
Comparison of two countries and educational systems
Extended case study
Extended case study
Extended case study
Extended case study Extended case study
Short report
Short report
Continued
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No. 2nd Issue E2
(Country) Authors Names Hubwieser, Armoni, Giannakos
2-1
(India) Raman, Smrithi, Achuthan, Nedungadi
2-2
(Korea) An, Choi, Lee
2-3
(NRW, Germany) Knobelsdorf, Magenheim, Brinda, Engbring, Humbert, Pasternak, Schroeder, Thomas, Vahrenhold (Finland) Vihavainen, Kurhila
2-4
2-5
(USA) Repenning, Webb, Koh, Nickerson, Miller, Brand, Her Many Horses, Basawapatna, Gluck, Grover, Gutierrez, Repenning
Title
Type
How to Implement Rigorous Computer Science Education in K-12 Schools? Some Answers and Many Questions Computer Science (CS) Education in Indian Schools: Situation Analysis using Darmstadt Model Computing Education in Korea—Current Issues and Endeavors Computer Science Education in North-Rhine Westphalia, Germany—A Case Study
Editorial of associate and guest editors
A Purposeful MOOC to Alleviate Insufficient CS Education in Finnish Schools Scalable Game Design: A Strategy to Bring Computer Science Education to Schools through Game Design and Simulation Creation
Extended case study of extracurricular initiative
Extended case study
Extended case study
Extended case study
Extended Case Study of extracurricular initiative
Table II. The Complete DM [Hubwieser et al. 2014] No 1
2
Dim. 3: Educational relevant areas Educational system Organizational aspects of subject Degree of compulsion Enrollment School type
Sociocultural-Related Factors History of ICT and Informatics in School Age Gender Social and immigration background Family socialization Public opinion Technoeconomic development
Keywords The type of school: Primary School, High School, Gymnasium, Grammar School, etc., and its location in the respective school system; compulsory subject, optional subject or course, chosen out of a list of choices, integrated into other subjects, how many years the course comprises, how many lessons per week and time per lesson. Enrollment in the course or subject that is described or as a consequence of the described activity regarding further enrollment in advanced CS courses Preconditions of that are set by the society, the parents, and the students, didactical approaches in the past, limitations of abstraction caused by the cognitive development of the students (e.g., according to the theory of Piaget [14]); diversity aspects, beliefs, attitudes, concerns of the parents, the general opinion towards CS and ICT that is common in the respective social environment, the degree that technology and its usage has made its way into the society, for example, the percentage of households that are equipped with computers and internet access or the functions or software types that are available to the students at home. Continued
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Table II. Continued No 3
4
Dim. 3: Educational relevant areas Policies Research and funding policies Education policies Enhancing cooperation Technical infrastructure Financing initiatives Quality management Teacher Qualification Teacher education CS teacher education Certification Training Professional experience
5
Motivation Student Teacher
6
Intentions Standards Competencies CSE Interdisciplinary Learning objectives Knowledge CS ICT
7
8
Curriculum Issues
9
Examination/Certification
10
Teaching Methods CSE General education Extracurricular Activities Contest
11
12
13
Media Technical infrastructure Textbooks Tools Didactical software Visualization software Unplugged Media Haptic media Research (Outcomes/Effects)
Keywords Political initiatives and strategies, structural reform projects, experimental school types, influence of industry or universities
Education at universities versus pedagogical colleges, curricula and standards for teacher education, mandatory degrees in CS or pedagogy, teacher examination, recruitment strategies, percentage of active teachers with such degrees, additional teaching subjects required, in-service training strategies, profile of professional experience of the active teachers Correspondence between motivation and other factors (gender, age, social or ethnic background), strategies to increase students’ and teachers’ motivation Intention of policies and projects versus intentions of the teaching units; proposals for standards, implementation of those in curricula, competency models, stages, development and definitions, learning objectives, taxonomies, categories Definition of knowledge, representation forms (e.g., mind maps, concept maps), taxonomies (e.g., factual, conceptual, procedural, metacognitive), measurement, development, prerequisite of competencies. Curriculum design processes, forms, levels, categories, order and arrangement of knowledge elements, distribution over grades and months, combination and interleaving of knowledge, intentions, methods and media Graduation levels, examination formats, centralization versus school autonomous examinations, standards and strategies, certification levels and purposes Suggestions of pedagogical or professional methods, for example, working methods, learning and teaching methods Industry internships, regional, national and international contests (e.g., Informatics Olympiad, Bebra Contest, Bundeswettbewerb Informatik) Electronic or “classical,” digital or analog resources, means, tools, facilities, equipment, aids, auxiliaries, accessories that enhance, leverage, or support learning processes, documentations of best practice, examples for CS unplugged, “Abenteuer Informatik”, “Informatik im Kontext”, programming languages, software systems, hardware applications Results of research project that provide evidence for outcomes, associations, relationships, or coherencies between the other categories.
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ACM Transactions on Computing Education, Vol. 15, No. 2, Article 5, Publication date: April 2015.
