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Part VI Conclusions 347
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Aalto University publication series
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Abstract Aalto University, P.O. Box
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Acknowledgements Lauri Malmi first
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4.5.3 Some effects of cognitive loa
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13.1.2 It is simple to watch an ani
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18.2.3 We saw a few pedagogically i
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11.16 PlanAni .....................
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Chapter 1 Here is How to Make Sense
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On research traditions Each researc
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The thesis should ideally be read f
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Introduction to Part I Introductory
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Figure 2.1: Bloom’s taxonomy of l
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2.2 The SOLO taxonomy sorts learnin
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2.2.3 The expected outcomes of prog
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Multi-institutional studies In the
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3.3 But many students do not learn
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long-term, action research study of
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Introduction to Part II What is inv
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Figure 4.1: A commonly used basic a
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play a decisive role in how and whe
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cognitive psychology also sought to
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terms for the two meanings. Followi
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It suggests that the growth of expe
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work (because of lack of motivation
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The effect of prior knowledge: the
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“writing a computer program is le
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model of program comprehension to o
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Chapter 5 Psychologists Also Say: W
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• are commonly deficient in a num
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expert stage. De Kleer and Brown ch
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5.3 Teachers employ conceptual mode
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Not only are there different notion
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the computer can carry out deductio
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Therefore: teach early and teach lo
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epresentation of a complex program
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A reasonable description of this fo
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are “somewhat contrary to the cla
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memory storage (see, e.g., Greeno,
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Chapter 6 Constructivists Say: Know
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Figure 6.1: A classification of con
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Social constructivist reasoning tak
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Figure 6.2: A radical destructivist
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certainly fall under the broad usag
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in the eyes of the members of the c
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of proper design, coding style, req
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In any particular course you will b
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precedes construction. Therefore, c
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Skirmish 7: minimal guidance pedago
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Chapter 7 Phenomenographers Say: Le
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the phenomenon. An individual’s e
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(Bowden and Marton, 2004). A way of
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The answer is none in particular, w
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Table 7.3: Different ways of experi
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7.6 Phenomenography has not escaped
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outcome spaces describe both the st
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Figure 8.1: Views from three tradit
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There is substantial agreement betw
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• it may mark boundaries in ‘co
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Telling TCs apart from other conten
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et al., 2007). The latter was later
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Part III Teaching Introductory Prog
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Chapter 10 CS1 is Taught in Many Wa
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it and right from the beginning. So
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10.1.3 Guidance mediates complexity
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10.2 Some approaches foster schema
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Many CS1 teachers have come up with
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Vagianou (2006) observes that a wea
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Figure 10.6: A view of Anchor Garde
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impressions of computing matter and
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The paradigm shift There is anecdot
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notional machines. Sajaniemi and Ku
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Program visualization vs. algorithm
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Figure 11.2: A part of Kelleher and
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aspects can play a decisive part in
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Table 11.1: The original engagement
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The 2DET The engagement taxonomy of
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Given content means that the learne
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Table 11.5: A summary of selected p
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Figure 11.4: The PyDev debugger for
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Figure 11.6: DynaLab executing a To
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Figure 11.10: The user has just com
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Figure 11.11: Korsh and Sangwan’s
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Figure 11.14: JIVE displays various
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Figure 11.16: PlanAni executing a P
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Figure 11.18: A snapshot of a Java
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Figure 11.19: Jeliot 3 executing a
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Figure 11.21: The Teaching Machine
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students used VIP in the way intend
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Python in the browser: Jype and the
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11.3.3 A few systems make the stude
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Figure 11.31: Students interact wit
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Online Tutoring System Kollmansberg
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Figure 11.36: A “Clouds & Boxes
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Table 11.7: Experimental evaluation
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Introduction to Part IV We have now
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An example Here is a short Python c
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Chapter 13 The UUhistle System Faci
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194 Figure 13.1: An animation of a
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Figure 13.2: The between-step stage
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Figure 13.4: UUhistle highlights a
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Figure 13.7: UUhistle’s interacti
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13.4 Teachers can turn examples int
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Add another +, then the literal 1.
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Figure 13.11: The user has created
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Figure 13.14: A VPS assignment in t
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Figure 13.16: A visual algorithm si
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Chapter 14 Visual Program Simulatio
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the individual instructions of the
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Visual program simulation seeks to
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14.2.2 VPS exercises can have eleme
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features prominently in many progra
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too, later decided to develop a sof
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The easiest examples for a programm
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may be necessary; at the very least
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Figure 14.1 continued M. H. van Emd
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integration of new material with pr
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The system designer vs. excessive d
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Level 3 By allowing what’s wrong.
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about this mistake to the user in a
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Table 15.1: Cognitive dimensions of
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parts that deal with different stag
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Error-proneness A VPS exercise in U
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something that resides ‘within th
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evidence. Like the documentation of
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Introduction to Part V Reflecting o
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launched for sharing (e.g., Fincher
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elatively independent of the resear
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There are values that are internal
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• Authenticity is an abstraction
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• Triangulation: triangulation of
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Each assignment was worth a number
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Figure 16.1: The earlier version of
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Chapter 17 Students Perceive Visual
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Figure 17.1: The phenomenographic r
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Figure 17.4: The structure of human
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Figure 17.5: The structure of aware
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further note the importance of esta
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Whichever variant of the analysis p
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Different phenomenographers define
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choose what to do?”, “What does
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We sought to form an outcome space
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17.4.1 A: VPS is perceived as learn
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17.4.2 B: VPS is perceived as learn
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Interviewer 2 : Can you describe ho
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17.4.5 E: VPS is perceived as learn
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through VPS is perceived as learnin
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Table 17.2: Qualitatively different
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what the phenomenon is in reality,
Page 304 and 305: the students develop a sophisticate
Page 306 and 307: involve VPS). 17 • The teacher us
Page 308 and 309: thought about the dynamics of VPS.
Page 310 and 311: solve the assignments using the ani
Page 312 and 313: Table 18.1: Types of information us
Page 314 and 315: As they start to work on the first
Page 316 and 317: print third second = third As they
Page 318 and 319: Elizabeth: And. . . So the function
Page 320 and 321: Otto: “True”. . . And then we g
Page 322 and 323: The pair fail to accommodate refere
Page 324 and 325: Parameter passing was the only topi
Page 326 and 327: 18.3 We have some quantitative resu
Page 328 and 329: and the student searches for meanin
Page 330 and 331: in Section 18.2.4 is a step in this
Page 332 and 333: Chapter 19 UUhistle Helps Students
Page 334 and 335: • The supervising research assist
Page 336 and 337: Table 19.1: Improvement from ‘non
Page 338 and 339: - attempts to make variables get th
Page 340 and 341: to predict program behaviors better
Page 342 and 343: • The use of programs with a doma
Page 344 and 345: in the course more generally, not o
Page 346 and 347: Good both as an idea and in functio
Page 348 and 349: In many cases the UUhistle assignme
Page 350 and 351: Boredom and excessive detail A fair
Page 352 and 353: A handful of students suggested tha
Page 356 and 357: Introduction to Part VI In Parts I,
Page 358 and 359: as an important component of introd
Page 360 and 361: 21.5 The contribution of the thesis
Page 362 and 363: the picture is hardly complete. Fut
Page 365 and 366: Part VII Appendices 357
Page 367 and 368: On Table A.1 In Table A.1, topics o
Page 369 and 370: Table A.1 continued No. Topic Descr
Page 377 and 378: Appendix B Example Programs from Co
Page 379 and 380: Assignment 4.1 (animation) def gree
Page 381 and 382: def refuel(self, liters): actually_
Page 383 and 384: Appendix C Example Programs from Ex
Page 385 and 386: Q4 (pretest and post-test) def tral
Page 387 and 388: Already now, and especially in the
Page 389 and 390: Appendix E Statement of the Author
Page 391 and 392: Anderson, J. R., Conrad, F. G., and
Page 393 and 394: Bennedsen, J. and Schulte, C. (2006
Page 395 and 396: Bower, M. (2008). A Taxonomy of Tas
Page 397 and 398: Clancy, M. (2004). Misconceptions a
Page 399 and 400: Dönmez, O. and İnceoğlu, M. M. (
Page 401 and 402: Fleury, A. E. (1991). Parameter Pas
Page 403 and 404: Green, T. R. G. and Petre, M. (1996
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Hundhausen, C. D. (2002). Integrati
Page 407 and 408:
Karavirta, V. (n.d.). XAAL: eXtensi
Page 409 and 410:
Kumar, A. N. (2005). Results from t
Page 411 and 412:
Lister, R. and Leaney, J. (2003). I
Page 413 and 414:
Mayer, R. E. and Alexander, P. A. (
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Myller, N. and Bednarik, R. (2006).
Page 417 and 418:
Pashler, H., McDaniel, M., Rohrer,
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Proulx, V. K. and Cashorali, T. (20
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Rossy de Brito, S., Silva, A. S., d
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Schumacher, R. M. (1987). Acquisiti
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Smith, P. A. and Webb, G. I. (2000)
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Thompson, E. (2008). How Do They Un
Page 429 and 430:
von Glasersfeld, E. (1998). Why Con
Page 432:
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