Proposal view
| Proposal Type: | Individual Paper |
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| Domain: | Learning and Cognitive Science |
| SIG: | Learning and Instruction with Computers |
| Type | Submitted Paper |
| Equipment |
PC and projector |
| Paper Details |
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| Title | Improving Students’ Working Memory, Fluid Intelligence, and Science Achievement through Computerized Cognitive Training |
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| Abstract | Working memory (WM) is a cognitive system responsible for simultaneously maintaining and manipulating information during cognitive activity (Baddeley & Hitch, 1974). It contains both attention control and memory storage capacities (Engle, Tuholski, Laughlin, & Conway, 1999). It has been found to be closely related to fluid intelligence and science achievement (Yuan, Steedle, Shavelson, Alonzo, & Oppezzo, in press). Historically, working memory capacity (WMC) was assumed to be fixed. A recent study found computerized cognitive training (CCT) could significantly increase WMC and fluid intelligence of children with attention-deficit/hyperactivity disorder (ADHD) in a clinical setting. This study examined whether regular students would significantly improve their WM, fluid intelligence, and science achievement, through CCT in a school setting. Thirty-seven seventh and eighth grade middle-school students participated in a pretest-posttest controlled experiment to examine whether CCT would significantly improve their WM. Students were randomly assigned to either experimental or control groups after they took measures of WM, fluid intelligence, and science achievement. Experimental group students took CCT on WM, while control group students studied computerized science lessons and low level CCT on WM. Students in both groups were trained for 24.65 days on average. Students were retested with the same tests at end of training. Analyses of covariance (ANCOVA) examined whether experimental group students made significantly greater improvements on WM, fluid intelligence, and science achievement than did control group students. Results confirmed that students improved their memory storage and attention control, with more improvement in the former than the latter. A tentative connection between CCT tasks and performance on WM measures was observed. No substantial changes were observed in fluid intelligence or science achievement. We recommend adding dual-type training exercises to further enhance CCT’s impact on WM, fluid intelligence, and science achievement. |
| Summary | Introduction Working memory (WM) is responsible for temporarily maintaining and manipulating information during cognitive activity (Baddeley, 2002). It is composed of information storage and attention control processes (Engle, Tuholski, Laughlin, & Conway, 1999). Both simple memory span tasks and dual-tasks have been used to measure working memory capacity (WMC), although the former are commonly considered measures of short-term memory (STM), while the latter are viewed as better measures of WM. Prior studies found that WMC is strongly related to an array of advanced cognitive abilities, including fluid intelligence, critical thinking, learning (Kyllonen, 2002; Kyllonen & Christal, 1990), and academic achievement in reading, mathematics, and science (Gathercole, Pickering, Knight, & Stegmann, 2004; Johnstone & Al-Naeme, 1991; Swanson & Howell, 2003). Due to the importance of WM in cognition, an individual’s performance will be affected when the cognitive load exceeds his/her WMC (Sweller, 1994). To eliminate the restricting effect of WMC in cognitive activity, some researchers try to reduce the cognitive load (Sweller, van Merrienboer, & Paas, 1998), while others explore ways to improve WMC (Ericsson & Kintsch, 1995; Klingberg et al., 2005). Although WMC was previously considered unchangeable, recent studies found that people could improve their WMC through extensive training (Ericsson, 1980; Ericsson & Kintsch, 1995). Klingberg et al. (2005) reported that children with attention-deficit/hyperactivity disorder (ADHD) significantly improved their WMC and fluid intelligence through computerized cognitive training (CCT) in a clinical setting. This study explored whether regular middle-school students would improve their WMC, fluid intelligence, and science achievement through CCT in a school setting. Methods A randomized pretest-posttest controlled experiment was carried out in a middle school in northern California between January and March 2006. Fifty-one seventh and eighth grade middle-school students were randomly assigned to the experimental or control group after pretesting on measures of WM, fluid intelligence, and science achievement. Experimental group students participated in CCT of WM; control group students worked on alternating computerized science lessons and low level WM training. Students trained for 30-40 minutes per day, for an average total of 24.65 days. The thirty-seven students who chose to remain in the study (thus forgoing elective courses) were retested at the end of the training. Experimental group students trained with RoboMemoÒ (2005, Cogmed Cognitive Medical Systems AB, Stockholm, Sweden), a multimedia program for Windows designed to improve WM. Students completed 115 trials in eight exercises per day. The program included visuospatial, numerical, and verbal tasks, and automatically adjusted task difficulty to match a student’s WMC level. Control group students worked on computerized science lessons and a similar training program MegaMemoÒ (2005, Cogmed Cognitive Medical Systems AB, Stockholm, Sweden) alternately. In the computerized science lessons, students watched videos and answered questions about science topics such as Bears, Reptiles, Carbon, and Earthquakes. Every other day, students completed low level WM training using MegaMemo, which presented the same training exercises as those in RoboMemo but the difficulty was kept at a very low level. Training was implemented in a school computer lab that contained 11 laptops and 8 Macintosh computers, laid out in a U-shape against three sides of the room. Laptops were separated from each other by an unused Macintosh computer. Students sat individually at tables facing the wall and wore headphones when they worked on the training tasks. This setting effectively prevented distractions during the training. Seven trained coaches were randomly assigned to a specific student and supervised his/her training. A structured reward program including daily rewards (stickers), weekly rewards (candy or a pencil), and biweekly rewards (a party) was implemented to motivate students to work hard during the training. Coaches conducted individual feedback meetings with students twice per week to discuss the students’ performance in the training and future improvement goals. The six measures used at both pretest and posttest included Span-board Task (Klingberg et al., 2005), computerized Auditory Number Span Task (Ekstrom et al., 1976), Automated Operation Span (Conway et al., 2005; Unsworth et al., 2005), Automated Reading Span (Conway et al., 2005; Unsworth et al., 2005), Raven’s Progressive Matrices Plus (Raven, 1998), and a science achievement test developed to assess the California science content standards. The internal consistency reliabilities of the six measures ranged from 0.76 to 0.89. Results Correlation coefficients among pretest scores confirmed prior findings about the strong associations among WM, fluid intelligence, and science achievement. Result from exploratory factor analysis of the WM measures was consistent with finding from prior studies that dual-tasks assess more attention control than do simple memory span tasks. Analyses of covariance (ANCOVA) examined the training effect. The results showed CCT significantly improved regular students’ verbal and spatial memory capacity, with an effect size of 0.68 and 0.47, respectively. CCT also improved students’ combined memory storage and attention control, on average, although the improvement was not statistically significant,. Analyses also showed students’ performance on different types of training exercises and scores on dissimilar WM measures was correlated. In addition, students did not show significant mean increases in their fluid intelligence or science achievement following training. There are several possible reasons for this: the lack of a significant increase in combined memory storage and attention control, WM might not be a bottleneck for regular students in cognitive activities as it is for children with ADHD, time delay in the transfer of WM changes into improvement in fluid intelligence and science achievement, and the importance of content knowledge in performance on the science achievement test. Conclusions and Implications This study has both important theoretical and practical implications. Theoretically, it supports the plasticity of WM and confirms the difference between dual-tasks and simple memory span tasks. Practically, this study found that regular students could improve their WM through CCT in a school setting. This represents an endeavor to apply technology and research results from cognitive psychology in educational settings to enhance human cognitive capacity. One practical training recommendation is to incorporate more dual-type tasks in CCT for regular school students because this may increase the likelihood of observing the hypothesized improvements in fluid intelligence and scientific achievement. |
| Keywords | Cognitive skills Computer-supported learning environments Science education |
| Appendices | References.doc |
| Authors | ||||||
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| Name | Surname | Institution | Country | EARLI Number | Presenting | |
| Kun | Yuan | Stanford University | United States | katyuan@hotmail.com | * | |
| Richard | Shavelson | Stanford University | United States | richs@stanford.edu | ||
| Alicia | Alozo | the University of Iowa | United States | alicia-alonzo@uiowa.edu | ||
| Jeffrey | Steedle | Stanford University | United States | jsteedle@stanford.edu | ||
