Difference between revisions of "Sequencing learning with multiple representations of rational numbers (Aleven, Rummel, & Rau)"

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| '''Total Participant Hours''' || ~2100
 
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| '''Data available in DataShop''' || [https://pslcdatashop.web.cmu.edu/DatasetInfo?datasetId=325 Dataset: Fraction Study Spring 2009 (log data only)][https://pslcdatashop.web.cmu.edu/DatasetInfo?datasetId=296 Dataset: Mathtutor Fractions MERs Spring 2009 (revised)]
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* '''Pre/Post Test Score Data:''' No
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Revision as of 16:37, 6 December 2010

Sequencing learning with multiple representations of rational numbers

Vincent Aleven, Nikol Rummel, and Martina Rau

Summary Table

Study 1

PIs Vincent Aleven & Nikol Rummel
Other Contributers Graduate Students: Martina Rau (CMU HCII)
Study Start Date September 1st, 2008
Study End Date August 31st, 2009
Number of Students ~350
Total Participant Hours ~2100
Data available in DataShop Dataset: Fraction Study Spring 2009 (log data only)Dataset: Mathtutor Fractions MERs Spring 2009 (revised)
  • Pre/Post Test Score Data: No
  • Paper or Online Tests: online
  • Scanned Paper Tests: NA
  • Blank Tests: No
  • Answer Key: No


Abstract

We investigate a key issue in coordinative learning, namely, how learning with multiple external representations (MERs) should be sequenced to effectively support students’ conceptual understanding. In order to benefit from MERs, learners must attain some level of fluency in interpreting and manipulating the individual representations, and must also engage in sense making across the representations to relate them and abstract underlying concepts. The question arises how tasks involving different representations should be sequenced so that both these aspects of robust learning are realized. In particular, how frequently should students switch between representations? We focus on fractions as a challenging topic area for students in which multiple representations are often used and likely to support robust learning. This research will contribute to the literature on early mathematics learning, learning with multiple representations, and learning with intelligent tutoring systems. It will also add to the portfolio of studies in the PSLC’s coordinative learning cluster.

Background & Significance

A quintessential form of coordinative learning occurs when learners work with multiple external representations (MERs) of subject matter. Accumulating evidence points towards the promise of learning with MERs (Ainsworth, Bibby, & Wood, 2002; Larkin & Simon, 1987; Seufert, 2003), and also to the need for students to make sense out of the different representations by connecting and abstracting from them (Ainsworth, 1999).
This research focuses on a difficult area of early mathematics learning: fractions. Both teachers’ experiences and research in educational psychology show that students have difficulties with fraction arithmetic and with the various representations for fractions (e.g. Brinker, 1997; Callingham & Watson, 2004; Caney & Watson, 2003; Person et al., 2004; Pitta-Pantazi, Gray & Christou, 2004). Coordinating between MERs is regarded as a key process for learning across areas of mathematics (Kilpatrick, Swafford, & Findell, 2001; NCTM, 2000), including fractions (e.g. Kieren, 1993; Moss & Case, 1999; Martinie & Bay-Williams, 2003; Thompson & Saldanha, 2003).
A number of authors have argued, based on observational studies, that MERs can lead to deeper conceptual understanding of fractions (Corwin et al., 1990; Cramer et al., 1997a, 1997b; Steiner & Stoeckling, 1997). However, we know of no experimental studies that have investigated the advantages of instruction with multiple (graphical) fraction representations over instruction that focuses on a single representation, with one exception: an in vivo experiment, in which 132 6th-grade students used four versions of CTAT-built tutors (Rau, Aleven, & Rummel, 2009). Students learning with MERs and prompted to self-explain performed best on a posttest and delayed posttest assessing procedural and conceptual knowledge of fractions.
At this point, however, we do not know enough about the circumstances that may influence the effectiveness of learning with multiple representations of fractions, a criticism that has been leveraged against the existing body of research on learning with MERs more generally (Ainsworth, 2006; Goldman, 2003). The proposed research looks at how the development of fluency with any given representation interacts with sense making across representations. First, as Ainsworth (2006) points out, being able to interpret a particular type of representation is a prerequisite for learning from it. However, such ‘representational fluency’ does not just emerge by itself, but requires practice. Second, it is important that students engage in sense making across the different representations to relate them and integrate the information they provide (Ainsworth, 2006; Brinker, 1997; Paik, 2005; Uttal et al., 1997). According to cognitive flexibility theory (Spiro & Jehng, 1990), being presented with MERs challenges the learner to switch between different perspectives on the same concepts. Under this perspective, learning with MERs supports the development of robust – flexible and transferable – knowledge (Kaput, 1989), to the extent that learners coordinate between the representations, that is, cognitively link the information the MERs provide and abstract underlying conceptual knowledge. A key question is therefore whether learners should build up fluency with each representation first, before they engage in sense-making activities aimed at coordinating representations, or whether they develop more flexible knowledge when they become familiar with the different representations in parallel and continuously engage in sense making across representations. This potential conflict is inherent in designing instruction with MERs.


Glossary

  • Conceptual knowledge: knowledge about the rationale of a solution procedure
  • Procedural knowledge: knowledge of the components of a correct procedure involving knowledge about step-by-step actions for solving problems

Research questions

When learning with multiple external representations, do students learn more robustly when new representations are introduced gradually, with (highly) infrequent switching between representations, or when the representations are introduced right from the start, with students switching often between representations? Or, is a transition from infrequent to frequent switching between representations most beneficial?

Hypotheses

  • We hypothesize that a mix of these two designs (i.e., an intermediate position on the continuum between highly infrequent and highly frequent switching between the representations) would be best as it allows learners to gain some experience with one representation before moving on to the next, but also facilitates making connections across representations as the (temporal) distance between representations is smaller than in the highly infrequently switching design.
  • We hypothesize that gaining fluency with each of the representations is more important at the beginning of a tutoring session than towards the end. Therefore, we expect a sequence that transitions from infrequent to frequent switching between representations to be more effective than the extremes of the continuum between highly infrequent and highly infrequent switching between the representations.

Dependent variables

  • Previously validated pretest, immediate posttest, and delayed posttest measuring student performance on:
    • Reproduction of conceptual knowledge
    • Reproduction of procedural knowledge
    • Transfer of conceptual knowledge
    • Transfer of procedural knowledge
  • Log data collected during tutor use, used to assess:
    • Learning curves
    • Time on task
    • Error rates
    • Hint usage
    • Latency of responses

Independent Variables

  1. Switch frequently – students will switch representations after every other tutor problem.
  2. Switch with moderate frequency – students will switch representations after every 5 tutor problems
  3. Switch infrequently – within each unit of the tutor curriculum, the representations are used in a “blocked” manner: students first work with one representation, then with the next, then with the third
  4. Switch with gradually-increasing frequency – students start out within each unit by switching representations with moderate frequency (as in the second condition), but the frequency increases gradually until at the end of each unit it reaches the same frequency as the first condition

Findings

Data collection is still in progress.

Explanation

Data collection is still in progress.

Further Information

Connections

Annotated Bibliography

References

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  • Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183-198.
  • Ainsworth, S. (in press). How do animations influence learning? In Robinson & Schraw (Eds.), Current Perspectives on Cognition, Learning, and Instruction: Recent Innovations in Educational Technology that Facilitate Student Learning.
  • Ainsworth, S., Bibby, P., & Wood, D. (2002). Examining the effects of different multiple representational systems in learning primary mathematics. Journal of the Learning Sciences, 11(1), 25-61.
  • Bodemer, D., Ploetzner, R., Bruchmüller, K., & Häcker, S. (2005). Supporting learning with interactive multimedia through active integration of representations. Instructional Science, 33(1), 73-95.
  • Bodemer, D., & Faust, U. (2006). External and mental referencing of multiple representations. Computers in Human Behavior, 22(1), 27-42.
  • Brinker, L. (1997). Using Structured Representations To Solve Fraction Problems: A Discussion of Seven Students' Strategies.
  • Callingham, R., & Watson, J. (2004). A Developmental Scale of Mental Computation with Part-Whole Numbers. Mathematics Education Research Journal, 16(2), 69-86.
  • Caney, A., & Watson, J. M. (2003). Mental Computation Strategies for Part-Whole Numbers. Paper presented at the International Educational Research Conference, Auckland, New Zealand.
  • Corwin, R. B., Russell, S. J., & Tierney, C. C. (1990). Seeing fractions: A unit for the upper elementary grades. Sacramento, CA: California Dept. of Education. (ED 348 211).
  • Cramer, K., Behr, M., Post, T., & Lesh, R. (1997a). Rational Number Project: Fraction Lessons for the Middle Grades: Level 1. Dubuque, IA: Kendall/Hunt Publishing.
  • Cramer, K., Behr, M., Post, T., & Lesh, R. (1997b). Rational Number Project: Fraction Lessons for the Middle Grades: Level 2. Dubuque, IA: Kendall/Hunt Publishing.
  • Goldman, S. R., Mertz, D. L., & Pellegrino, J. W. (1989). Individual differences in extended practice functions and solution strategies for basic addition facts. Journal of Educational Psychology, 81(4), 481-496.
  • Kaput, J.J. (1989). Linking representations in the symbolic systems of algebra. In S. Wagner & C. Kieran (Eds.), Research agenda for mathematics education: Research issues in the learning and teaching of algebra (pp.167-194). Reston, VA: National Council of Teachers of Mathematics.
  • Kieren, T. E. (1993). Rational and fractional numbers: From quotient fields to recursive understanding. In T. P. Carpenter, E. Fennema, & T. A. Romberg (Eds.), Rational numbers: An integration of research (pp. 49-84). Hillsdale, NJ: Erlbaum.
  • Kilpatrick, Jeremy; Swafford, Jane; Findell, Bradford (Eds.); Mathematics Learning Study Committee, National Research Council (2001). Conclusions and recommendations. In Adding It Up: Helping Children Learn Mathematics (pp. 407-432). Washington, D.C.: The National Academies Press.
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  • Martinie, S.L., & Bay-Williams, J.M. (2003) Investigating students’ conceptual understanding of decimal fractions using multiple representations. Mathematics Teaching in the Middle School, 8(5), 244-248.
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