Tony Yeigh Centre for Children & Young People School of Education Southern Cross University

1. 2008 Cognitive Load Theory Conference UOW February 29 – March 1, 2008 Presentation: Distracted Learners & Instructional Design» The problem» How I investigated it» What I found» What I think this means Tony Yeigh Centre for Children & Young People School of Education Southern Cross University NSW, Australia

2. The Problem: Context & Background Effective learning appears to be connected to the ability to selectively focus attention on information relating to a task, an aspect of cognition key to the learning process, and generally associated with the working memory (WM) system (Byrnes, 2001; Byrnes & Fox, 1998). However, selective attentional processing actually involves two complimentary yet distinct cognitive mechanisms: the activation of task-relevant information (Baddeley, 2001), & the inhibition of task-irrelevant information (Passolunghi et al, 1999). The mechanism of interest for this research is cognitive inhibition, which allows the learner to attend to task-relevant information whilst simultaneously ignoring task-irrelevant information in the face of interference and distraction.(Dempster & Brainerd, 1995; Harnishfeger & Bjorklund, 1994).

3. The Problem: Inhibition Defined Cognitive inhibition is a term commonly used to refer to the suppression of distracting or non-relevant information during on-task cognitive engagement. Noted that distinctions are made in the professional literature concerning the respective roles of inhibition (Dempster, 1991) and interference(D’Esposito et al, 1999). The term inhibition (CI) is used here as a generalised term, and conceptualised as a functional connection between items of information where, when two or more items are competing for attentional focus, one of the items needs to be suppressed (C/F Dempster, 1993; Harnishfeger & Bjorklund, 1994; Mecklinger et al, 2003).

4. The Problem: Why CI? • A great deal of research has been invested in exploring the relationship between WM processes and learning, yet most of this has been directed at: • Issues of memory or memory function (Anderson, 2000; Ericsson, Chase, & Faloon, 1980; Reynolds, 1993; Rose, 1992) • The limited capacity of WM and the attentional system (Baddeley, 1986; Spear & Riccio, 1994; Just & Carpenter, 1987) • The relationship between selective attention and the automatic processing of information (Sweller, 1999; Stanovich, 2000) • How the meaningful elaboration of information is constructed (Kintsch, 1988; Pressley & Wharton-McDonald, 1997)

5. The Problem: Why CI? (cont.) • As well, a great deal of research investigating WM in relation to learning has focused on why the learning is easier or more difficult in relation to: • Development (e.g., Swanson, 1999; Towse, Hitch, & Hutton, 1998) • Task difficulty and strategy use (Chi, Glaser, & Rees, 1982; Guttentag, 1997; Miller, 1994) • Specific learning difficulties (Gathercole & Pickering, 2000; Pennington & Ozonoff, 1996)

6. The Problem: Why CI? (My Focus) In contrast, little has been done in the way of connecting CI to: Specific classroom learning (although related studies have been carried out on interference and the nature of forgetting, see Greene, 1992; Waugh & Norman, 1965). WM function in relation to irrelevant information processing (although see Barrouillet, Fayol, & Lathuliere, 1997; Mecklinger et al, 2003; Passolunghi, Cornoldi, & de Liberto, 1999; Swanson, Cooney, and Brock, 1993). None of these, however, has attempted to profile the underlying relationships between inhibitory differences (differences in students’ ability to inhibit distracting information), and cognitive load (how much mental effort the students experience in relation to the instruction).

7. A Key Problem: Instructional Encoding WM research indicates that the way in which information is organised has a significant effect on how individuals are “primed” for processing it (Brown, 1979; Roediger, Neely, & Blaxton, 1983), I postulate that well formatted instructional organisation represents a type of implicit priming, while poorly formatted organisation results in instructional ambiguity…

8. Instructional Ambiguity: Some Examples The teacher presenting relevant and irrelevant information without distinction Asking questions in a way that gives irrelevant or distracting semantic cues to students Using words that have multiple referents available (in terms of specific identity, tense, or contextual use) Making only weak semantic associations to technical or “jargonesque” (domain-specific) words (C/F Neil et al, 1995) Failing to define intra-categorical information used in relation to advance organisers or in relation to classroom questioning ☻Example ofinstructional ambiguity(please use the supplied handout to record your results)

9. Instructional Ambiguity: Rote Memory Test A

10. Instructional Ambiguity: Rote Memory Test B

11. Implicit Priming: A Case of Instructional Organisation? This is a simple test of maths ability. At the end of the test you will be asked a question… Answer it immediately. Do not stop to think about it…just record the very first thing that pops into your mind… Following the instructions… & as quickly as possible!

12. Implicit Priming: Begin Maths… Do not write or try to write or remember the answers, just solve the following calculations using your mind… 15 + 6 3 + 56 89 + 2 12 + 53 75 + 26 !!! 25 + 52 63 + 32

13. Implicit Priming: Calculations are such hard work!!...But its nearly over… Come on, one more… 123 + 5 NOW QUICK!... THINK ABOUT A COLOUR AND A TOOL! (Write the FIRST THING you thought of)

14. How I Investigated the Problem • Proposition: Differing instructional approaches of individual teachers, because they entail various amounts of processing ambiguity, can be expected to place differential cognitive demands on the limited capacity WM system of students, due to variations in the amount of inhibitory activity required. • I chose to investigate this by: • measuring inhibitory function across a range of mixed ability students • Measuring how hard the students had to work, mentally, in order to process instructional information under each of four different teachers

15. The CL Ratings

16. How I Investigated the Problem (cont.) In addition to these measures, I also had the teachers report individual student achievement outcomes, to see if I could get an idea as to whether the differences in inhibitory function were impacting upon how well the students achieved academically.

17. Overview of Proposed Relationships

18. Overview of Variable Measures

19. What I Found: Results (H1) My first hypothesis predicted that a significant, positive relationship would exist between general WM function and student achievement outcomes, proposing that academic achievement is predicted from WM functionality. Significant relationships were found for all the measured WM functions (overall capacity, memory recall, problem-solving accuracy, & speed of processing) in relation to academic achievement marks. This finding is in agreement with a body of information that indicates the generalised importance of WM to the teaching and learning process, and links this research to the established body of knowledge concerning WM & learning.

20. H1: Results Correlations between word recall & math's accuracy were significant, r(114) = .37, p < .01. Correlations between math’ accuracy & attentional conflict were significant and negative, r(114) = -.26, p < .05, as was the correlation between word recall & attentional conflict , r(114) = -.23, p < .05.

21. What I Found: Results (H2) My second hypothesis predicted that a positive relationship would exist between CI and the students’ cognitive load (CL) ratings concerning how “hard” they had to work, mentally, to achieve learning outcomes under the participating teachers. Mixed results were obtained for the CI x CL correlations, yet significant relationships were found for three out of the four participating teachers, suggesting that a close connection does exist between the inhibitory function and mental effort.

22. Results (H2)(cont.) This relationship was predicted on the basis that: Higher CI scores indicate less efficient processing of distracting information, with lower CI scores indicating more efficient processing of distracting information. Higher CL ratings indicate greater mental effort, with lower CL ratings indicating less mental effort. Thus, in general, less efficient inhibitors were expected to experience greater cognitive load for instructional processing than the more efficient inhibitors. This relationship was confirmed for the students under three out of the four teachers involved in the study.

23. H2: Results Student cognitive load (CL) ratings across the four teachers were mixed in relation to their attentional conflict (CI) scores: For (T1) this relationship was significant (r[114] = .26, p < .05), for T2 it was significant (r[114] = .29, p < .05), and for T3 it was also significant (r[114] = .21, p < .05). However, for T4 this relationship was not significant (r[114] = .17, p > .05).

24. What I Found: Results (H3) My third hypothesis proposed that student inhibitory ability (CI) would interact with mental effort (CL), to significantly influence achievement outcomes. Again a mixed bag was found, with ANOVAS returning only one clearly significant interaction of this sort (for T2), yet also with a clear trend evident in this direction (for T1). Of interest here is that T2 is the least experienced teacher in the study, and the same teacher for whom the strongest correlation occurred with respect to how much cognitive load (CL) the students experienced. As well, T1 is the most experienced teacher in the study, and received the second-lowest CL rating from the students.

25. H3:Results A within-subjects ANOVA, using Achievement x CI x CL, returned F(23,7) = 3.26, p < .06, η2 = .41. A post hoc analysis (Tukeys HSD) suggests that most of this trend is driven by the relationship between CI and achievement (r[114] = -.23, p > .05). Note that this relationship is negative, suggesting that the more efficient inhibitors (receiving lower conflict scores) were obtaining higher achievement outcomes, while the less efficient inhibitors (receiving higher conflict scores) were obtaining lower achievement outcomes, overall.

26. What I Think This Means… The main finding here is that students more efficient at inhibition also experienced less cognitive load in relation to their learning. In addition, the relationship between CI & CL may have influenced the students achievement outcomes in relation to the instruction of T2, and, to a lesser degree, to T1. These findings may well signify that inhibition needs to be taken more directly into account when designing instruction, and especially as the instruction concerns students less able to inhibit distracting information.

27. What I Think This Means…CI as a Moderator of Learning? On the basis of the overall findings here, I offer a (tentative) model of instructional processing (next slide) that is aimed at depicting a moderating effect for the relation between CI & CL. The model proposes that, whereas attentional processing directly mediates the relationship between instruction and achievement, the relationship between cognitive inhibition and cognitive load further moderates this relationship. What this model suggests, is that a student’s ability to handle attentional distracters needs to be more explicitly acknowledged as a distinctive element within the overall design of instruction.

28. What I Think This Means…The Model T4 T3 Attentional Processing Instruction CI X CL T2 T1 Learning

29. Rote Memory Test(Instructional Ambiguity) Words remembered from 1st test Words remembered from 2nd test …What made the difference?

30. Implicit Priming Task Your Answer? _____________________________ _____________________________

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33. References (cont.) Just, M. A. & Carpenter, P. A. (1987). The psychology of reading and language comprehension. Boston, MA: Allyn & Bacon. Kintsch, W. (1988). The role of knowledge in discourse comprehension: A construction-integration model. Psychological Review, 95(2), 163-182. Mecklinger, A., Weber, K., Gunter, T. C., & Engle, R. W. (2003). Dissociable brain mechanisms for inhibitory control: Effects of interference content and working memory capacity. Cognitive Brain Research, 18(1), 26-38. Miller, P. H. (1994). Individual differences in children’s strategic behavior: Utilization deficiencies. Learning and Individual Differences, 6, 285-307. Neil, W. T., Valdes, L. A., & Terry, K. M. (1995). Selective attention and the inhibitory control of cognition. In F. N. Dempster and C. J. Brainerd (Eds.), Interference and inhibition in cognition (pp. 207-261). New York: Academic Press. Passolunghi, M. C., Cornoldi, C., & De Liberto, S. (1999). Working memory and intrusions of irrelevant information in a group of specific poor problem solvers. Memory & Cognition, 27, 779-790. Pennington, B. F., & Ozonoff, S. (1996). Executive functions and developmental psychopathology. Journal of Child Psychology and Psychiatry and Allied Disciplines, 37(1), 51-87.

34. References (cont.) Pressley, M. & Wharton-McDonald, R. (1997). Skilled comprehension and its development through instruction. School Psychology Review, 26, 448-466. Reynolds, R. E. (1993). Selective attention and prose learning: Theoretical and empirical research. Educational Psychology Review, 4(4), 345 – 391. Roediger, H. L, Neely, J. H., & Blaxton, T. A. (1983). Inhibition from related primes in semantic memory retrieval: A reappraisal of Brown’s (1979) paradigm. Journal of Experimental Psychology: Learning, Memory, and Cognition, 9, 478-485. Rose, S. (1992). The making of memory: From molecules to mind. New York: Anchor Books. Spear, N.E. & Riccio , D.C. (1994) Memory: Phenomena and principles. Needham Heights, MA: Allyn & Bacon. Stanovich, K. E. (2000). Progress in understanding reading: Scientific foundations and new frontiers. New York: Guilford Press. Swanson, H. L. (1999). What develops in working memory?: A life span perspective. Developmental Psychology, 35(4), 986-1000. Swanson, H. K., Cooney, J. B., & Brock, S. (1993). The influence of working memory and classification ability on children’s word problem solutions. Journal of Experimental Child Psychology, 55, 374-395. Sweller, J. (1999). Instructional design in technical areas. Camberwell, VIC: The Australian Council for Educational Research LTD. Towse, J. N., Hitch, G. J., & Hutton, U. (1998). A re-evaluation of working memory capacity in children. Journal of Memory and Language, 39, 195 – 217. Waugh, N. C., & Norman, D. A. (1965). Primary memory. Psychological Review, 72(3), 89-104.

35. Thanking You!