University of Groningen

The effectiveness of hints during computer supported word problem solvingde Kock, Willem Daniel

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problem solving: A theoretical model. European Journal of Psychology

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Capuano, N., D’Aniello, G., Gaeta, A., & Miranda, S. (2015). A personality based

adaptive approach for information systems. Computers in Human Behavior,

44, 156–165. doi:10.1016/j.chb.2014.10.058

Chang, K., Sung, Y., & Lin, S. (2006). Computerassisted learning for mathematical

problem solving. Computers & Education, 46, 140–151.

doi:10.1016/j.compedu.2004.08.002

Cheng, X., Li, Y., Sun, J., & Huang, J. (2015). Application of a novel collaboration

engineering method for learning design: A case study. British Journal of

Educational Technology, 47 (4), 803818.

Chung, K. K. H., & Tam, Y. H. (2005). Effects of cognitivebased instruction on

mathematical problem solving by learners with mild intellectual disabilities.

Journal of Intellectual and Developmental Disability, 30, 207–216.

doi:10.1080/13668250500349409

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book M7]. Arnhem, The Netherlands: Citogroep.

Clarebout, G., & Elen, J. (2006). Tool use in computerbased learning

environments. Computers in Human Behavior, 22, 389–411.

doi:10.1016/j.chb.2004.09.007.

212 213

Baker, R. S., Corbett, A. T., & Koedinger, K. R. (2004). Detecting student misuse of

intelligent tutoring systems. In J. C. Lester, R. M. Vicario, & F. Paraguaçu

(Eds.), Proceedings of seventh international conference on intelligent

tutoring systems, ITS 2004 (pp. 531–540). Berlin: Springer Verlag.

Baker, R. S., Walonoski, J., Heffernan, N., Roll, I., Corbett, A., & Koedinger, K. R.

(2008). Why students engage in "gaming the system" behavior in interactive

learning environments. Journal of Interactive Learning Research, 19 (2),

185–224. doi:10.1.1.297.2912

Bannert, M., Hildebrand, M., & Mengelkamp, C. (2009). Effects of a metacognitive

support device in learning environments. Computers in Human Behavior,

25 (4), 829–835. doi:10.1016/ j.chb.2008.07.002.

Bannert, M., Sonnenberg, C., Mengelkamp, C., & Pieger, E. (2015). Short and long

term effects of students’ selfdirected metacognitive prompts on navigation

behavior and learning performance. Computers in Human Behavior, 52,

293306. doi: 10.1016/j.chb.2015.05.038

Barron, B. (2000). Achieving Coordination in Collaborative ProblemSolving

Groups. Journal of Learning Sciences, 9 (4), 403–436.

Berthold, K., Nückles, M., & Renkl, A. (2007). Do learning protocols support

learning strategies and outcomes? The role of cognitive and metacognitive

prompts. Learning and Instruction, 17, 564–577.

Bollen, L., Gijlers, H., & Van Joolingen, W. (2012). Computersupported

collaborative drawing in primary school education – Technical realization

and empirical findings. In V. Herskovic, H. U. Hoppe, M. Jansen & J. Ziegler

(Eds.), Collaboration and technology (pp. 1–16). Berlin Heidelberg:

Springer.

Boonen, A.J.H., Van Wesel, F., Jolles, J. & Van der Schoot, M. (2014). The role of

visual representation type, spatial ability and reading comprehension in

word problem solving: An itemlevel analysis in primary school children.

International Journal of Educational Research, 68, 15–26.

Briggs, R. O., De Vreede, G. J. , Nunamaker, J. F. Jr. , & Tobey, D. (2001).

ThinkLets: Achieving Predictable, Repeatable Patterns of Group

Interaction with Group Support Systems (GSS). Proceedings of the

Hawaii International Conference on System Sciences, Los Alamitos, IEEE

Computer Society Press.

Bruun, F. (2013). Elementary Teachers’ Perspectives of Mathematics Problem

Solving Strategies. The Mathematics Educator. 23 (1), 45–59.

Bulu, S. T. & Pedersen, S. (2010). Scaffolding middle school students' content

knowledge and illstructured problem solving in a problembased

hypermedia learning environment. Educational Technology Research and

Development, 58(5), 507–529.

Capraro, R. M., Capraro, M. M., & Rupley, W. H. (2012). Reading enhanced word

problem solving: A theoretical model. European Journal of Psychology

of Education, 27 (1) , 91 114. doi:10.1007/s10212 011 0068 3

Capuano, N., D’Aniello, G., Gaeta, A., & Miranda, S. (2015). A personality based

adaptive approach for information systems. Computers in Human Behavior,

44, 156–165. doi:10.1016/j.chb.2014.10.058

Chang, K., Sung, Y., & Lin, S. (2006). Computerassisted learning for mathematical

problem solving. Computers & Education, 46, 140–151.

doi:10.1016/j.compedu.2004.08.002

Cheng, X., Li, Y., Sun, J., & Huang, J. (2015). Application of a novel collaboration

engineering method for learning design: A case study. British Journal of

Educational Technology, 47 (4), 803818.

Chung, K. K. H., & Tam, Y. H. (2005). Effects of cognitivebased instruction on

mathematical problem solving by learners with mild intellectual disabilities.

Journal of Intellectual and Developmental Disability, 30, 207–216.

doi:10.1080/13668250500349409

CITO. (2002). RekenenWiskunde 2002. Opgavenboekje M7[Mathematics work

book M7]. Arnhem, The Netherlands: Citogroep.

Clarebout, G., & Elen, J. (2006). Tool use in computerbased learning

environments. Computers in Human Behavior, 22, 389–411.

doi:10.1016/j.chb.2004.09.007.

214 215

Clarebout, G., Elen, J., Johnson, W. L., & Shaw, E. (2002). Animated pedagogical

agents: An opportunity to be grasped? Journal of Educational Multimedia

and Hypermedia, 11, 267–286.

Clark, H., & Brennan, S. (1991). Grounding in communication. In L. B. Resnick, J.

Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp.

127–149). Washington, DC: APA.

Clark, R. C., & Mayer, R. E. (2011). Elearning and the science of instruction. (3rd

ed.). San Francisco: John Wiley & Sons, Inc.

Cohen, D., & Hill, H. (2000). Instructional policy and classroom performance: The

mathematics reform in California. Teachers College Record, 102, 294–343.

Cohen, J (1988). Statistical Power Analysis for the Behavioral Sciences (second

ed.). Lawrence Erlbaum Associates.

Cooper, B., & Harries, T. (2005). Making sense of realistic word problems:

Portraying working class “failure” on a division with remainder problem.

International Journal of Research & Method in Education, 28, 147–169

Corbalan, G., Kester, L., & Van Merriënboer, J. J. G. (2008). Selecting learning

tasks: Effects of adaptation and shared control on efficiency and task

involvement. Contemporary Educational Psychology, 33, 733–756.

Corter, J. E. & Zahner, D. (2007). Use of external visual representations in

probability problem solving. Statistics Education Research Journal, 6 (1),

2250.

Crippen, K. J., & Earl, B. L. (2007). The impact of Webbased worked examples and

selfexplanation on performance, problem solving, and selfefficacy.

Computers & Education, 49 (3), 809–821.

doi:10.1016/j.compedu.2005.11.018

DarlingHammond, L., Wei, R. C., & Johnson, C. M. (2009). Teacher preparation

and teacher learning: A changing policy landscape. In G. Sykes, B. L.

Schneider, & D. N. Plank (Eds.), Handbook of education policy research (pp.

613–636). New York, NY: Routledge.

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of educational interventions on students’ academic performance: a meta

analysis. Review of Educational Research, 84 (4), 509 545.

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Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (pp. 507–

523). New York, NY: Cambridge University Press.

De Kock, W. D., & Harskamp, E. G. (2014). Can Teachers in Primary Education

Implement a Metacognitive Computer Programme for Word Problem

Solving in their Mathematics Classes? Educational Research and

Evaluation, 20 (3), 231–250. doi:10.1080/13803611.2014.901921

Demetriadis, S.N., Papadopoulos, P.M., Stamelos, J.G., & Fischer, F. (2008). The

effect of scaffolding students’ contextgenerating cognitive activity in

technologyenhanced casebased learning. Computers and Education, 51 (2),

939–954.

Desoete, A., Roeyers, H., & De Clercq, A. (2003). Can offline metacognition

enhance mathematical problem solving? Journal of Educational

Psychology, 95, 188–200.doi:10.1037/00220663.95.1.188

Devolder, A., Van Braak, J., & Tondeur, J. (2012). Supporting selfregulated

learning in computerbased learning environments: Systematic review of

effects of scaffolding in the domain of science education. Journal of

Computer Assisted Learning, 28, 557–573.

De Vreede, G. J., Kolfschoten, G. L., & Briggs, R. O. (2006). ThinkLets: a

collaboration engineering pattern language. International Journal of

Computer Applications in Technology, 25 (2), 140154.

Dignath, C., & Büttner, G. (2008). Components of fostering selfregulated learning

among students. A metaanalysis on intervention studies at primary and

secondary school level. Metacognition and Learning, 3, 231–

264.doi:10.1007/s114090089029x

Dillenbourg, P., & Tchounikine, P. (2007). Flexibility in macro CSCL scripts.

Journal of Computer Assisted Learning, 23 (1), 113.

Ding, N. (2009). Computersupported collaborative learning and gender

(Doctoral dissertation). Groningen: University of Groningen.

Ding, N., Bosker, R. J., & Harskamp, E. G. (2011). Exploring gender and gender

pairing in the knowledge elaboration processes of students using computer

supported collaborative learning. Computers & Education, 56 (2), 325–336.

214 215

Clarebout, G., Elen, J., Johnson, W. L., & Shaw, E. (2002). Animated pedagogical

agents: An opportunity to be grasped? Journal of Educational Multimedia

and Hypermedia, 11, 267–286.

Clark, H., & Brennan, S. (1991). Grounding in communication. In L. B. Resnick, J.

Levine, & S. D. Teasley (Eds.), Perspectives on socially shared cognition (pp.

127–149). Washington, DC: APA.

Clark, R. C., & Mayer, R. E. (2011). Elearning and the science of instruction. (3rd

ed.). San Francisco: John Wiley & Sons, Inc.

Cohen, D., & Hill, H. (2000). Instructional policy and classroom performance: The

mathematics reform in California. Teachers College Record, 102, 294–343.

Cohen, J (1988). Statistical Power Analysis for the Behavioral Sciences (second

ed.). Lawrence Erlbaum Associates.

Cooper, B., & Harries, T. (2005). Making sense of realistic word problems:

Portraying working class “failure” on a division with remainder problem.

International Journal of Research & Method in Education, 28, 147–169

Corbalan, G., Kester, L., & Van Merriënboer, J. J. G. (2008). Selecting learning

tasks: Effects of adaptation and shared control on efficiency and task

involvement. Contemporary Educational Psychology, 33, 733–756.

Corter, J. E. & Zahner, D. (2007). Use of external visual representations in

probability problem solving. Statistics Education Research Journal, 6 (1),

2250.

Crippen, K. J., & Earl, B. L. (2007). The impact of Webbased worked examples and

selfexplanation on performance, problem solving, and selfefficacy.

Computers & Education, 49 (3), 809–821.

doi:10.1016/j.compedu.2005.11.018

DarlingHammond, L., Wei, R. C., & Johnson, C. M. (2009). Teacher preparation

and teacher learning: A changing policy landscape. In G. Sykes, B. L.

Schneider, & D. N. Plank (Eds.), Handbook of education policy research (pp.

613–636). New York, NY: Routledge.

De Boer, H., Donker, A. S., & Van der Werf, M. P. C. (2014). Effects of the attributes

of educational interventions on students’ academic performance: a meta

analysis. Review of Educational Research, 84 (4), 509 545.

De Jong, T. (2005). The Guided Discovery Principle in Multimedia learning. In R.

Mayer (Ed.), The Cambridge Handbook of Multimedia Learning (pp. 507–

523). New York, NY: Cambridge University Press.

De Kock, W. D., & Harskamp, E. G. (2014). Can Teachers in Primary Education

Implement a Metacognitive Computer Programme for Word Problem

Solving in their Mathematics Classes? Educational Research and

Evaluation, 20 (3), 231–250. doi:10.1080/13803611.2014.901921

Demetriadis, S.N., Papadopoulos, P.M., Stamelos, J.G., & Fischer, F. (2008). The

effect of scaffolding students’ contextgenerating cognitive activity in

technologyenhanced casebased learning. Computers and Education, 51 (2),

939–954.

Desoete, A., Roeyers, H., & De Clercq, A. (2003). Can offline metacognition

enhance mathematical problem solving? Journal of Educational

Psychology, 95, 188–200.doi:10.1037/00220663.95.1.188

Devolder, A., Van Braak, J., & Tondeur, J. (2012). Supporting selfregulated

learning in computerbased learning environments: Systematic review of

effects of scaffolding in the domain of science education. Journal of

Computer Assisted Learning, 28, 557–573.

De Vreede, G. J., Kolfschoten, G. L., & Briggs, R. O. (2006). ThinkLets: a

collaboration engineering pattern language. International Journal of

Computer Applications in Technology, 25 (2), 140154.

Dignath, C., & Büttner, G. (2008). Components of fostering selfregulated learning

among students. A metaanalysis on intervention studies at primary and

secondary school level. Metacognition and Learning, 3, 231–

264.doi:10.1007/s114090089029x

Dillenbourg, P., & Tchounikine, P. (2007). Flexibility in macro CSCL scripts.

Journal of Computer Assisted Learning, 23 (1), 113.

Ding, N. (2009). Computersupported collaborative learning and gender

(Doctoral dissertation). Groningen: University of Groningen.

Ding, N., Bosker, R. J., & Harskamp, E. G. (2011). Exploring gender and gender

pairing in the knowledge elaboration processes of students using computer

supported collaborative learning. Computers & Education, 56 (2), 325–336.

216 217

Donker, A. S., De Boer, H., Kostons, D., DignathVan Ewijk, C. C., & Van der Werf,

M. P. (2014). Effectiveness of learning strategy instruction on academic

performance: a metaanalysis. Educational Research Review, 11, 1–26.

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R. Sternberg & BenZeev (Eds). The Nature of Mathematical Thinking.

Hillsdale, NY: Lawrence Erlbaum Associates.

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with multiple representations. The Physics Teacher, 35 (5), 270275.

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Problem: Graphic Representations and Problem Solving. Science and School

Mathematics Journal, 108 (5), 184–193.

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tell us about the learning process? Educational Research Review, 1, 314.

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for collaborative and argumentative writing. In E. de Corte (Ed.), Powerful

learning environments (pp. 159–177). Amsterdam: Pergamon.

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videoconferencing environments: The role of external representation tools.

Paper presented at the Computer Support for Collaborative Learning:

Foundations for a CSCL Community Conference, Boulder, CO., University of

Munrich, Germany

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(2008). Problem solving and computational skill: Are they shared or distinct

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30–47. doi:10.1037/00220663.100.1.30

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& Hamlett, C. L. (2010a). The effects of strategic counting instruction, with

and without deliberate practice, on number combination skill among

students with mathematics difficulties. Learning and Individual Differences,

20, 89–100. doi:10.1016/j.lindif.2009.09.003

Fuchs, L. S., Powell, S. R., Seethaler, P. M., Cirino, P. T., Fletcher, J. M., Fuchs,

D.,…Zumeta, R. O. (2009). Remediating number combination and word

problem deficits among students with mathematics difficulties: A

randomized control trial. Journal of Educational Psychology, 101, 561–576.

doi:10.1037/a0014701

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represent word problems with algebraic equations: A randomized control

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performance: a metaanalysis. Educational Research Review, 11, 1–26.

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R. Sternberg & BenZeev (Eds). The Nature of Mathematical Thinking.

Hillsdale, NY: Lawrence Erlbaum Associates.

Dufresne, R. J. & Gerace, W. J. & Leonard, W. J. (1997). Solving physics problems

with multiple representations. The Physics Teacher, 35 (5), 270275.

Edens, K. & Potter, E. (2008). How Students "Unpack" the Structure of a Word

Problem: Graphic Representations and Problem Solving. Science and School

Mathematics Journal, 108 (5), 184–193.

Efklides, A. (2006). Metacognition and affect: What can metacognitive experiences

tell us about the learning process? Educational Research Review, 1, 314.

Erkens, G., Kanselaar, G., Prangsma, M., & Jaspers, J. (2003). Computer support

for collaborative and argumentative writing. In E. de Corte (Ed.), Powerful

learning environments (pp. 159–177). Amsterdam: Pergamon.

Fischer, F., & Mandl, H. (2002). Facilitating knowledge convergence in

videoconferencing environments: The role of external representation tools.

Paper presented at the Computer Support for Collaborative Learning:

Foundations for a CSCL Community Conference, Boulder, CO., University of

Munrich, Germany

Foshay, R., & Kirkley, J. (2003). Principles for teaching problem solving

(Technical Paper No. 4). Retrieved from PLATO Learning

website:http://www.learningace.com/doc/2440565/e094c08dc4a564128df

491521b5d4ef8/2003_foshay_platolearninginc_techpaper4_principles

forteachingproblemsolving

Fuchs, L. S., Fuchs, D., Stuebing, K., Fletcher, J. M., Hamlett, C. L., & Lambert, W.

(2008). Problem solving and computational skill: Are they shared or distinct

aspects of mathematical cognition? Journal of Educational Psychology, 100,

30–47. doi:10.1037/00220663.100.1.30

Fuchs, L. S., Powell, S. R., Seethaler, P. M., Cirino, P. T., Fletcher, J. M., Fuchs, D.,

& Hamlett, C. L. (2010a). The effects of strategic counting instruction, with

and without deliberate practice, on number combination skill among

students with mathematics difficulties. Learning and Individual Differences,

20, 89–100. doi:10.1016/j.lindif.2009.09.003

Fuchs, L. S., Powell, S. R., Seethaler, P. M., Cirino, P. T., Fletcher, J. M., Fuchs,

D.,…Zumeta, R. O. (2009). Remediating number combination and word

problem deficits among students with mathematics difficulties: A

randomized control trial. Journal of Educational Psychology, 101, 561–576.

doi:10.1037/a0014701

Fuchs, L. S., Zumeta, R. O., Schumacher, R. F., Powell, S. R., Seethaler, P. M.,

Hamlett, C. L., & Fuchs, D. (2010b). The effects of schemabroadening

instruction on second graders’ wordproblem performance and their ability to

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Team Cognition: Understanding the Factors that Drive Process and

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Learning in Solving Physics Problems. International Journal of Science

Education, 28 (14), 1669–1688.

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multimedia learning apply to science classrooms? Learning and Instruction,

17 (5), 465–477. doi:10.1016/j.learninstruc.2007.09.010.

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student motivation and learning? Educational Research Review, 6, 27–54.

doi:10.1016/j.edurev.2010.07.004.

Hegarty, M & Kozhevnikov, M. (1999). Types of visual–spatial representations and

mathematical problem solving. Journal of Educational Psychology, 91 (4),

684–689. doi:10.1037/00220663.91.4.684

Hegarty, M., Mayer, R. E., & Monk, C. A. (1995). Comprehension of

arithmetic word problems: A comparison of successful and

unsuccessful problem solvers. Journal of Educational Psychology,

87, 1832.

Hill, J. R. & Hannafin, M. J. (2001). Teaching and learning in digital environments:

the resurgence of resourcebased learning. Educational Technology

Research and Development, 49 (3), 37–52.

HmeloSilver, C. E., Chinn, C.A., Chan, C. K. & O’Donnell, A. (2013). The

International Handbook of Collaborative Learning. Routledge, New York.

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people need more maths for today’s jobs. London.

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mathematical problem solving. The Journal of Educational Research, 95,

374–380. doi:10.1080/00220670209596612

Hurme, T. R., & Järvelä, S. (2005). Student’s activity in computersupported

collaborative problem solving in mathematics. International Journal of

Computers for Mathematical Learning, 10, 49–73. doi: 10.1007/s10758005

45793

Inspectie van het Onderwijs. (2008). Basisvaardigheden rekenenwiskunde in het

basisonderwijs [Basic math skills in elementary education]. Utrecht, The

Netherlands: Author.

Jacobs, V. R., Franke, M. L., Carpenter, T. P., Levi, L., & Battey, D. (2007).

Professional development focused on children’s algebraic reasoning in

elementary schools. Journal for Research in Mathematics Education ,

38 (3), 258288.

Jacobse, A. E. (2012). Can we improve children’s thinking? (Doctoral dissertation).

Groningen, The Netherlands: University of Groningen.

Jacobse, A. E., & Harskamp, E. G. (2009). Studentcontrolled metacognitive

training for solving word problems in primary school mathematics.

Educational Research and Evaluation, 15, 447–463.

doi:10.1080/13803610903444519

Janssen, J. (2014). Opening the black box of collaborative learning: A meta

analysis investigating the antecedents and consequences of collaborative

interaction. Report no. 41111632 commissioned by NWOPROO and NRO.

University of Utrecht, Utrecht (2014)

Janssen, J., Erkens, G., & Kirschner, P. A. (2011). Group awareness tools: It’s what

you do with it that matters. Computers in Human Behavior, 27, 1046–1058.

doi:10.1016/j.chb.2010.06.002

Jitendra, A. K., Dupuis, D. N., Rodriguez, M. C., Zaslofsky, A. F., Slater, S., Cozine

Corroy, K., & Church, C. (2013). A randomized controlled trial of the impact

of schemabased instruction on mathematical outcomes for third grade

students with mathematics difficulties. The Elementary School Journal, 114

(2), 252–276.

220 221

Jitendra, A. K., PetersonBrown, S., Lein, A., Zaslofsky, A., Kunkel, A., Jung, PG.,

& Egan, A. (2015). Teaching mathematical word problem solving: The

quality of evidence for strategy instruction priming the problem structure.

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Effects of Collaboration Scripts and Heuristic Worked Examples on the

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Kramarski, B., & Friedman, S. (2014). Solicited versus Unsolicited Metacognitive

Prompts for Fostering Mathematical ProblemSolving Using Multimedia.

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supported in mathematical Elearning environments? Journal of Computer

Assisted Learning, 22, 24–33. doi:10.1111/j.13652729.2006.00157.x

Kroesbergen, E. H., & Van Luit, J. E. H. (2002). Teaching multiplication to low

math performers: Guided versus structured instruction. Instructional

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Ku, H., Harter, C., Liu, P., Thompson, L., & Cheng, Y. (2007). The effects of

individually personalized computerbased instructional program on solving

mathematics problems. Computers in Human Behavior, 23 (3), 1195–1210.

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& Egan, A. (2015). Teaching mathematical word problem solving: The

quality of evidence for strategy instruction priming the problem structure.

Journal of Learning Disabilities, 48 (1), 51–72.

Jitendra, A. K., Rodriguez, M., Kanive, R. G., Huang, JP., Church, C., Corroy, K. C.,

& Zaslofsky, A. F. (2013). The impact of smallgroup tutoring interventions

on the mathematical problem solving and achievement of third grade

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Jitendra, A. K., Star, J., Starosta, K., Leh, J., Sood, S., Caskie, G., & Mack, T.

(2009). Improving students’ learning of ratio and proportion problem

solving: The role of schemabased instruction. Contemporary Educational

Psychology, 34 (3), 250–264.

Johnson, D. W., & Johnson, R. T. (1999). Making cooperative learning work.

Theory into Practice, 38 (2), 67–73.

Johnson, D. W. & Johnson R. T. (2009). An Educational Psychology Success Story:

Social Interdependence Theory and Cooperative Learning. Educational

Researcher, 38, 365 – 379.

Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational

Technology Research and Development, 48 (4), 6385.

Jonassen, D. H. (2003). Using cognitive tools to represent problems. Journal of

Research on Technology in Education, 35 (3), 362381.

Jonassen, D. H. (2010). Learning to solve problems: A handbook. New York:

Routledge.

Kirschner, F., Paas, F., & Kirschner, P. A. (2009). A cognitive load approach to

collaborative learning: United brains for complex tasks. Educational

Psychological Review, 21, 31–42. doi:10.1007/s1064800890952

Koedinger, K. R., & Aleven, V. (2007). Exploring the assistance dilemma in

experiments with cognitive tutors. Educational Psychology Review, 19, 239–

264. doi:10.1007/s1064800790490.

Koedinger, K. R., & Nathan, M. J. (2004). The real story behind story problems:

Effects of representations on quantitative reasoning. Journal of the Learning

Sciences, 13, 129–164.

Kolfschoten, G. L., Vreede, G. J. de, Briggs, R. O., & Sol, H. G. (2010).

Collaboration ‘Engineerability’. Group Decision & Negotiation, 19 (3), 301

312.

Kollar I., Fischer F., & Hesse F. W. (2006). Collaboration scripts—A conceptual

analysis. Educational Psychology Review, 18, 159–185. doi:10.1007/s10648

00690072.

Kollar, I., Ufer, S., Reichersdorfer, E., Vogel, F., Fischer, F., & Reiss, K. (2014).

Effects of Collaboration Scripts and Heuristic Worked Examples on the

Acquisition of Mathematical Argumentation Skills of Teacher Students with

Different Levels of Prior Achievement. Learning and Instruction, 32, 2236.

Kramarski, B., & Friedman, S. (2014). Solicited versus Unsolicited Metacognitive

Prompts for Fostering Mathematical ProblemSolving Using Multimedia.

Journal of Educational Computing Research, 50 (3), 285–314.

Kramarski, B., & Gutman, M. (2006). How can selfregulated learning be

supported in mathematical Elearning environments? Journal of Computer

Assisted Learning, 22, 24–33. doi:10.1111/j.13652729.2006.00157.x

Kroesbergen, E. H., & Van Luit, J. E. H. (2002). Teaching multiplication to low

math performers: Guided versus structured instruction. Instructional

Science, 30, 361–378. doi:10.1023/A:1019880913714

Ku, H., Harter, C., Liu, P., Thompson, L., & Cheng, Y. (2007). The effects of

individually personalized computerbased instructional program on solving

mathematics problems. Computers in Human Behavior, 23 (3), 1195–1210.

Kyndt, E., Raes, E., Lismont, B., Timmers, F., Cascallar, E., & Dochy, F. (2013). A

metaanalysis of the effects of facetoface cooperative learning. Do recent

studies falsify or verify earlier findings? Educational Research Review,

10(0), 133149. doi:10.1016/j.edurev.2013.02.002

Larkin, J., & Simon, H. A. (1987). Why a diagram is (sometimes) worth ten

thousand words. Cognitive Science, 11, 6599.

222 223

Lee, H., Lim, K., & Grabowski, B. L. (2010). Improving selfregulation, learning

strategy use, and achievement with metacognitive feedback. Educational

Technology Research and Development, 58 (6), 629–648.

Lesh, R., & Doerr, H. (2000). Symbolizing, communicating and mathematizing:

Key components of models and modeling. In P. Cobb, E. Yackel, & K.

McClain (Eds.), Symbolizing and communicating in mathematics

classrooms (pp. 361–383). Mahwah, NJ: Lawrence Erlbaum.

Li, Q., & Ma, X. (2010). A metaanalysis of the effects of computer technology on

school students’ mathematics learning. Educational Psychology Review, 22,

215–243. doi:10.1007/s1064801091258

Lipponen, L., Rahikainen, M., Lallimo, J., & Hakkarainen, K. (2001). Analyzing

patterns of participation and discourse in elementary students’ online

science discussion. In P. Dillenbourg, A. Eurelings., & K. Hakkarainen (Eds.),

European Perspectives on ComputerSupported Collaborative Learning.

Proceedings of the First European Conference on CSCL (pp. 421428).

Maastricht, the Netherlands: Maastricht McLuhan Institute.

Liu, M., Bera, S., Corliss, S. B., Svinicki, M. D., & Beth, A. D. (2004).

Understanding the Connection Between Cognitive Tool Use and Cognitive

Processes as used by Sixth Graders in a ProblemBased Hypermedia

Learning Environment. Journal of Educational Computing Research, 31 (3),

309–334.

Low, R., & Over, R. (1989). Detection of missing irrelevant information within

algebraic story problems. Britisch Journal of Educational Psychology, 59

(3), 296–305.

Low, R., & Over, R. (1990). Text editing of algebraic word problems. Australian

Journal of Psychology, 42 (1), 63–73.

Lu, J., Lajoie, S. P., & Wiseman, J. (2010). Scaffolding problembased learning with

tools. International Journal of ComputerSupported Collaborative

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Makel, M. C., & Plucker, J. A. (2014). Facts are more important than novelty:

Replication in the education sciences. Educational Researcher, 43, 304–316.

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Among Reading, Mathematics, and Science Achievement at the Fourth

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H. Freeman.

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selfexplaining environment: what works in the design of agentbased

microworlds? Journal of Educational Psychology, 95, 806–813.

Mayer, R. E., & Hegarty, M. (1996). The process of understanding mathematical

problem solving. In: Sternberg, R. J. and BenZeev T., (Eds.), The nature of

mathematical thinking (pp. 29–54).Mahwah, NJ: Erlbaum.

Mayer, R. E., Mathias, A., & Wetzell, K. (2002). Fostering understanding of

multimedia messages through pretraining: Evidence for a twostage theory

of mental model construction. Journal of Experimental Psychology:

Applied, 8,147–154. doi:10.1037/1076898X.8.3.147

McLaren, B.M., van Gog, T., Ganoe, C., Karabinos, M., & Yaron, D. (2016). The

efficiency of worked examples compared to erroneous examples, tutored

problem solving, and problem solving in classroom experiments. Computers

in Human Behavior, 55, 8799. doi:10.1016/j.chb.2015.08.038

Meijer, J., & Riemersma, F. (2002). Teaching and testing mathematical problem

solving by offering optional assistance. Instructional Science, 30, 187–220.

Mevarech, Z. R., & Kramarski, B. (1997). IMPROVE: A multidimensional method

for teaching mathematics in heterogeneous classrooms. American

Educational Research Journal 34 (2), 365–394.

Mevarech, Z. R., & Kramarski, B. (2003). The effects of metacognitive training

versus workedout examples on students' mathematical reasoning. British

Journal of Educational Psychology, 73 (4), 449–471.

Montague, M., Enders C., & Dietz, S. (2011). Effects of cognitive strategy

instruction on math problem solving of middle school students with learning

disabilities. Learning Disability Quaterly, 34 (4), 262–272.

222 223

Lee, H., Lim, K., & Grabowski, B. L. (2010). Improving selfregulation, learning

strategy use, and achievement with metacognitive feedback. Educational

Technology Research and Development, 58 (6), 629–648.

Lesh, R., & Doerr, H. (2000). Symbolizing, communicating and mathematizing:

Key components of models and modeling. In P. Cobb, E. Yackel, & K.

McClain (Eds.), Symbolizing and communicating in mathematics

classrooms (pp. 361–383). Mahwah, NJ: Lawrence Erlbaum.

Li, Q., & Ma, X. (2010). A metaanalysis of the effects of computer technology on

school students’ mathematics learning. Educational Psychology Review, 22,

215–243. doi:10.1007/s1064801091258

Lipponen, L., Rahikainen, M., Lallimo, J., & Hakkarainen, K. (2001). Analyzing

patterns of participation and discourse in elementary students’ online

science discussion. In P. Dillenbourg, A. Eurelings., & K. Hakkarainen (Eds.),

European Perspectives on ComputerSupported Collaborative Learning.

Proceedings of the First European Conference on CSCL (pp. 421428).

Maastricht, the Netherlands: Maastricht McLuhan Institute.

Liu, M., Bera, S., Corliss, S. B., Svinicki, M. D., & Beth, A. D. (2004).

Understanding the Connection Between Cognitive Tool Use and Cognitive

Processes as used by Sixth Graders in a ProblemBased Hypermedia

Learning Environment. Journal of Educational Computing Research, 31 (3),

309–334.

Low, R., & Over, R. (1989). Detection of missing irrelevant information within

algebraic story problems. Britisch Journal of Educational Psychology, 59

(3), 296–305.

Low, R., & Over, R. (1990). Text editing of algebraic word problems. Australian

Journal of Psychology, 42 (1), 63–73.

Lu, J., Lajoie, S. P., & Wiseman, J. (2010). Scaffolding problembased learning with

tools. International Journal of ComputerSupported Collaborative

Learning, 5 (3), 283–298. doi:10.1007/s1141201090926

Makel, M. C., & Plucker, J. A. (2014). Facts are more important than novelty:

Replication in the education sciences. Educational Researcher, 43, 304–316.

doi:10.3102/0013189x14545513

Martin, M.O. & Mullis, I.V.S. (Eds.). (2013). TIMSS and PIRLS 2011: Relationships

Among Reading, Mathematics, and Science Achievement at the Fourth

Grade—Implications for Early Learning. Chestnut Hill, MA: TIMSS &

PIRLS International Study Center, Boston College.

Mayer, R. E. (1992) Thinking, problem solving, cognition (2nd Ed.). New York: W.

H. Freeman.

Mayer, R. E., Dow, G., & Mayer, S. (2003). Multimedia learning in an interactive

selfexplaining environment: what works in the design of agentbased

microworlds? Journal of Educational Psychology, 95, 806–813.

Mayer, R. E., & Hegarty, M. (1996). The process of understanding mathematical

problem solving. In: Sternberg, R. J. and BenZeev T., (Eds.), The nature of

mathematical thinking (pp. 29–54).Mahwah, NJ: Erlbaum.

Mayer, R. E., Mathias, A., & Wetzell, K. (2002). Fostering understanding of

multimedia messages through pretraining: Evidence for a twostage theory

of mental model construction. Journal of Experimental Psychology:

Applied, 8,147–154. doi:10.1037/1076898X.8.3.147

McLaren, B.M., van Gog, T., Ganoe, C., Karabinos, M., & Yaron, D. (2016). The

efficiency of worked examples compared to erroneous examples, tutored

problem solving, and problem solving in classroom experiments. Computers

in Human Behavior, 55, 8799. doi:10.1016/j.chb.2015.08.038

Meijer, J., & Riemersma, F. (2002). Teaching and testing mathematical problem

solving by offering optional assistance. Instructional Science, 30, 187–220.

Mevarech, Z. R., & Kramarski, B. (1997). IMPROVE: A multidimensional method

for teaching mathematics in heterogeneous classrooms. American

Educational Research Journal 34 (2), 365–394.

Mevarech, Z. R., & Kramarski, B. (2003). The effects of metacognitive training

versus workedout examples on students' mathematical reasoning. British

Journal of Educational Psychology, 73 (4), 449–471.

Montague, M., Enders C., & Dietz, S. (2011). Effects of cognitive strategy

instruction on math problem solving of middle school students with learning

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Willem de Kock was born in Leeuwarden, the Netherlands, on July 23th 1981. He

attended the Teacher’ Training College for Primary Education at NHL Hogeschool

from 2002 to 2006. After receiving his teacher degree, he continued his academic

career at the university. He did a premaster at the Institute for Pedagogical

Education (SPO), which is affiliated to the University of Groningen. After

completion, he enrolled in the Master programme of Educational Science at the

University of Groningen, specialising in the instructional design of learning

environments in education. He obtained his Master’s degree in Educational Science

at the University of Groningen in 2008. His thesis was about different methods for

teaching history using a digital whiteboard. Hereafter, he enrolled in the Research

Master programme of the University of Groningen, with Research and Evaluation

of Educational Effectiveness as his topic of interest. He obtained his Research

Master in 2009. During his master studies he worked as a research assistant on

different projects at the Groningen Institute for Educational Research (GION) of

the University of Groningen. After graduation, he continued his position at the

GION as a junior researcher. Here, he worked on the topic of improving the

effectiveness of computer support for students in mathematics education. In 2010,

he started his PhD project at the GION. Besides working on the studies presented

in this dissertation, he was involved in teaching a number of courses and

supervising master students. He is currently employed at NHL Hogeschool as a

lecturer (mathematics) with the Teacher’ Training College for Primary Education.