Maria Knobelsdorf, University of Dortmund, Germany - Didaktik der ...

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APPENDIX Table 4. The Factors, their Definitions and their items Factors Operational Definition Items Source Performance The degree to which an Using programming improves my performance in a task. (PE1) [18] Expectancy individual believes that Programming enhances my effectiveness in tasks progressing. (PE) attending the respective course is useful for him/her. (PE2) Programming would make it easier to complete a task. (PE3) Programming increases productivity in completing tasks. (PE4) Satisfaction The degree to which a I am satisfied with the programming experience. (STF1) [14] (STF) person positively feels with I am pleased with the programming experience. (STF2) the respective course. My decision to use programming was a wise one. (STF3) My feeling to use programming was good. (STF4) Social Influ- The degree to which an People who are important to me think that Ι should learn pro- [14] ence (SI) individual perceives that gramming. (SI1) most people who are im- People who influence my behavior encourage me to learn proportant to him think he should or should not attend the respective course. gramming. (SI2) Self-Efficacy The degree of conviction I could complete a programming task … [17] (SEF) that one can successfully if there was no one around to tell me what to do. (SEF1) execute the operation re- if I had only instructions for reference. (SEF2) quired to produce the outcomes. if I had never used it before. (SEF3) Behavioral The degree of students’ I intend to continue learning programming in the future. (BI1) [18] Intention (BI) willingness to attend the I will continue learning programming in the future. (BI2) respective course I will regularly learn programming in the future. (BI3) Confidence I feel confident in … Problem Solv- The degree of students’ understanding the problems presented to me. (CPS1) [11] ingConfidence (CPS) confidence to successfully cope with various problems identifying the components of a problem. (CPS2) analyzing a problem to other simpler ones. (CPS3) posing a problem, formulating it accurately and completely. (CPS4) Confidence The degree of students’ formulating the forms of conditional statement if. (CCC1) [11] for using Data Commands confidence to successfully use data commands discerning the differences of the forms of conditional statement if. (CCC2) (Conditional- selecting the best form of conditional statement depending on the Loop) problem. (CCC3) formulating the loop statement.(CLC1) selecting the best loop statement. (CLC2) using the appropriate loop statement. (CLC3) Confidence The degree of students’ deciding whether it is necessary to use an array. (CDS1) [11] for Data Struc- confidence to successfully selecting the formula of array (one‐dimensional, two‐ tures (CDS) use data structures dimensional, etc.). (CDS2) entering, processing and printing the items of an array. (CDS3) doing general exercises and exercises of searching and sorting using the structure of the array. (CDS4) defining the structures of the stack and queue with the correspondent operations. (CDS5) 24
Performance Expectancy (PE) Satisfaction (STF) Social Influence (SI) Self-Efficacy (SEF) Behavioral Intention (BI) Problem Solving Confidence (CPS) Confidence for using Data Commands (Conditional- Loop) Confidence for Data Structures (CDS) Table 5. Complete Results of the Games-Howell post hoc test Independent Variables Mean Std. (I) (J) Differ. (I-J) Error Sig. 3 rd Lyceum (GR) Gymnasium (GE) 0.35 0.38 0.63 Freshmen CS -1.51* 0.26 0.00 Gymnasium (GE) 3 rd Lyceum (GR) -0.35 0.38 0.63 Freshmen CS -1.86* 0.35 0.00 Freshmen CS 3 rd Lyceum (GR) 1.51* 0.26 0.00 Gymnasium (GE) 1.86* 0.35 0.00 3 rd Lyceum (GR) Gymnasium (GE) 0.38 0.36 0.55 Freshmen CS -0.87* 0.25 0.00 Gymnasium (GE) 3 rd Lyceum (GR) -0.38 0.36 0.55 Freshmen CS -1.25* 0.35 0.00 Freshmen CS 3 rd Lyceum (GR) 0.87* 0.25 0.00 Gymnasium (GE) 1.25* 0.35 0.00 3 rd Lyceum (GR) Gymnasium (GE) -0.39 0.42 0.62 Freshmen CS -1.66* 0.35 0.00 Gymnasium (GE) 3 rd Lyceum (GR) 0.39 0.42 0.62 Freshmen CS -1.26* 0.41 0.01 Freshmen CS 3 rd Lyceum (GR) 1.66* 0.35 0.00 Gymnasium (GE) 1.26* 0.41 0.01 3 rd Lyceum (GR) Gymnasium (GE) -0.19 0.35 0.86 Freshmen CS 0.24 0.25 0.61 Gymnasium (GE) 3 rd Lyceum (GR) 0.19 0.35 0.86 Freshmen CS 0.43 0.34 0.44 Freshmen CS 3 rd Lyceum (GR) -0.24 0.25 0.61 Gymnasium (GE) -0.43 0.34 0.44 3 rd Lyceum (GR) Gymnasium (GE) 0.54 0.46 0.47 Freshmen CS -2.29* 0.32 0.00 Gymnasium (GE) 3 rd Lyceum (GR) 0.54 0.46 0.47 Freshmen CS -1.75* 0.40 0.00 Freshmen CS 3 rd Lyceum (GR) 2.29* 0.32 0.00 Gymnasium (GE) 1.75* 0.40 0.00 3 rd Lyceum (GR) Gymnasium (GE) -0.32 0.33 0.60 Freshmen CS -0.54 0.24 0.07 Gymnasium (GE) 3 rd Lyceum (GR) 0.32 0.33 0.60 Freshmen CS -0.22 0.30 0.75 Freshmen CS 3 rd Lyceum (GR) 0.54 0.24 0.07 Gymnasium (GE) 0.22 0.30 0.75 3 rd Lyceum (GR) Gymnasium (GE) 0.40 0.34 0.47 Freshmen CS -0.41 0.27 0.29 Gymnasium (GE) 3 rd Lyceum (GR) -0.40 0.34 0.47 Freshmen CS -0.81 0.35 0.06 Freshmen CS 3 rd Lyceum (GR) 0.41 0.27 0.29 Gymnasium (GE) 0.81 0.35 0.06 3 rd Lyceum (GR) Gymnasium (GE) -0.56 0.39 0.33 Freshmen CS -0.98* 0.33 0.01 Gymnasium (GE) 3 rd Lyceum (GR) 0.56 0.39 0.33 Freshmen CS -0.42 0.43 0.61 Freshmen CS 3 rd Lyceum (GR) 0.98* 0.33 0.01 Gymnasium (GE) 0.42 0.43 0.61 *. The mean difference is significant at the 0.05 level. 25
Page 1 and 2: Fakultät für Mathematik, Informat
Page 3 and 4: Program Committee Michal Armoni Wei
Page 5 and 6: Challenge and Creativity: Students
Page 7 and 8: Challenges in Computer Science Educ
Page 9 and 10: These echo a 2008 report from the N
Page 11 and 12: examples, and in practice teachers
Page 13 and 14: Figure 3: A trace of bubble sort fr
Page 15 and 16: either their own program or another
Page 17 and 18: ital system used a variety of inter
Page 19 and 20: computer science, and with the less
Page 21 and 22: effect of different factors on the
Page 23: (GE) and freshmen CS and Lyceum (GR
Page 27 and 28: for active CS teachers. Furthermore
Page 29 and 30: participants change between the roo
Page 31 and 32: Altogether 830 participants visited
Page 33 and 34: 7. ACKNOWLEDGMENTS The initial equi
Page 35 and 36: • self-concept in science • ins
Page 37 and 38: mean at t0 mean at t2 mean at t0 me
Page 39 and 40: survey at the time t0 time of surve
Page 41 and 42: characteristics mean m (regarding t
Page 43 and 44: technology subjects in senior secon
Page 45 and 46: aim to react on these topics, exper
Page 47 and 48: the educational programs and ration
Page 49 and 50: y choice of handset, choice of netw
Page 51 and 52: 8. REFERENCES [1] Bell, T. et al. 2
Page 53 and 54: Agile Projects in High School Compu
Page 55 and 56: ited time, heterogeneous student ab
Page 57 and 58: the target audience. This phase is
Page 59 and 60: longer than one to two weeks (which
Page 61 and 62: e.g. assessing individual achieveme
Page 63 and 64: Conceptual Change and Epistemologic
Page 65 and 66: einterpreted, or excluded, for exam
Page 67 and 68: How Teachers in Different Education
Page 69 and 70: attended by about a 33-40 % of all
Page 71 and 72: The assumption of sphericity was no
Page 73 and 74: [23] Huynh, H. and Feldt, L. S. 197
Page 75 and 76:
Ways of Planning Lessons on the Top
Page 77 and 78:
other topic. The reasons given vari
Page 79 and 80:
Promoting Computational Thinking wi
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algorithm or a product is viewed as
Page 83 and 84:
Preparing Teachers for Teaching Inf
Page 85 and 86:
However, even when such learning th
Page 87 and 88:
Grand challenges for the UK: Upskil
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first two questions. We maintain th
Page 91 and 92:
(Some) Grand Challenges of Computer
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ecoming more student-centered. Inde
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[13] OECD. (2006). Are students rea
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in the world, for example, as descr
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The aims of the case study were to
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Figure 8: Acquisition of programmin
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The focus group girls were more con
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tool for teachers and students in t
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eledSQL - A New Web-Based Learning
Page 109 and 110:
create and manage teacher accounts.
Page 111 and 112:
ABSTRACT Bringing Contexts into the
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3.1.1 Greenfoot as a framework for
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Real-world context Views of Computi
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Real-world context GP Context Artif
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i. e. theories, models, frameworks,
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number P-156 in Lecture Notes in In
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1. Context-based education in compu
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Figure 1. Network traffic for authe
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A weak point of the Vigenère algor
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We have learnt that we can both loo
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Comparing CSTA K-12 Computer Scienc
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grade 4, 5, 6 or 8, depending on ch
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Table 1. Scoring Scale for the Impl
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the highest rate of implementation
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Information Theory on Czech Grammar
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of information in a message M, repr
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Data modeling and database systems
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the knowledge about ICT and CS (see
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The Mindstorm Effect: A Gender Anal
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Exploring the processing of formatt
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Teachersʼ Perceptions Of The Value
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Technocamps: Bringing Computer Scie
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Abenteuer Informatik - Hands-on exh
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Gaming and Mathematics: A Cross Cur
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Turi: Chatbot software for schools
Page 161 and 162:
ABSTRACT Learning Fields in Vocatio
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ABSTRACT This study examines the po
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