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Working Memory Load and Reminder Effect on Event-Based Prospective Memory of High- and Low-Achieving Students in Math

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Title: Working Memory Load and Reminder Effect on Event-Based Prospective Memory of High- and Low-Achieving Students in Math
Language: English
Authors: Chen, Youzhen, Lian, Rong, Yang, Lixian, Liu, Jianrong, Meng, Yingfang
Source: Journal of Learning Disabilities. Sep-Oct 2017 50(5):602-608.
Availability: SAGE Publications and Hammill Institute on Disabilities. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
Peer Reviewed: Y
Page Count: 7
Publication Date: 2017
Document Type: Journal Articles
Reports - Research
Education Level: Middle Schools
Descriptors: Short Term Memory, Cognitive Processes, Low Achievement, High Achievement, Mathematics Achievement, Middle School Students, Foreign Countries, Intelligence Tests, Visual Stimuli
Geographic Terms: China
Assessment and Survey Identifiers: Raven Progressive Matrices
DOI: 10.1177/0022219416668322
ISSN: 0022-2194
Abstract: The effects of working memory (WM) demand and reminders on an event-based prospective memory (PM) task were compared between students with low and high achievement in math. WM load (1- and 2-back tasks) was manipulated as a within-subject factor and reminder (with or without reminder) as a between-subject factor. Results showed that high-achieving students outperformed low-achieving students on all PM and n-back tasks. Use of a reminder improved PM performance and thus reduced prospective interference; the performance of ongoing tasks also improved for all students. Both PM and n-back performances in low WM load were better than in high WM load. High WM load had more influence on low-achieving students than on high-achieving students. Results suggest that low-achieving students in math were weak at PM and influenced more by high WM load. Thus, it is important to train these students to set up an obvious reminder for their PM and improve their WM.
Abstractor: As Provided
Number of References: 23
Entry Date: 2017
Accession Number: EJ1151502
Database: ERIC
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  Value: <anid>AN0124638941;led01sep.17;2017Aug17.13:02;v2.2.500</anid> <title id="AN0124638941-1">Working Memory Load and Reminder Effect on Event-Based Prospective Memory of High- and Low-Achieving Students in Math </title> <p>The effects of working memory (WM) demand and reminders on an event-based prospective memory (PM) task were compared between students with low and high achievement in math. WM load (1- and 2-back tasks) was manipulated as a within-subject factor and reminder (with or without reminder) as a between-subject factor. Results showed that high-achieving students outperformed low-achieving students on all PM and n-back tasks. Use of a reminder improved PM performance and thus reduced prospective interference; the performance of ongoing tasks also improved for all students. Both PM and n-back performances in low WM load were better than in high WM load. High WM load had more influence on low-achieving students than on high-achieving students. Results suggest that low-achieving students in math were weak at PM and influenced more by high WM load. Thus, it is important to train these students to set up an obvious reminder for their PM and improve their WM.</p> <p>Keywords: event-based prospective memory; low- and high-achieving students; working memory demand</p> <p>Prospective memory (PM) is the memory for intended actions to be performed at the appropriate time or situation in the future -- for example, remembering to bring one's homework and school utilities before going to school. PM tasks have been classified in a number of ways (Kvavilashvili & Ellis, 1996), but perhaps the most frequently used classification distinguishes between time- and event-based PM (Einstein & McDaniel, 1990). Event-based PM refers to intended actions to be performed when some external event occurs (e.g., remember to discuss something when meeting someone). Time-based PM refers to intended actions to be performed at a particular time (e.g., remember to attend a meeting at 4 p.m. tomorrow) or after a period of time. Because of the period between the formation and later realization of intentions, almost everyone encounters failures of PM, such as forgetting to attend a meeting, take some medicine, or perform some action in an emergency, which may result in serious negative consequences. In daily life, 70% of memory failures are PM failures.</p> <p>Some studies have shown that PM is significantly related to academic achievement. Low-achieving students, especially low achievers in math, report more PM problems than do high-achieving students (Chen, Liu, Wang, Shum, & Chan, 2014). Guo and Chen (2016) examined PM in students with learning disabilities and in low-achieving students. They found that students with math disability performed PM tasks in math as poorly as the low achievers. Both groups are weak in PM. They tend to forget to do their homework, submit their works before deadline, or neglect some steps when they meet some type of math problems. Such PM problems may bring much trouble to their lives and may decrease their academic achievements. It thus is very important to investigate what influence their PM has and how to help them improve it. This study is aimed at helping educators to (a) understand why students with low achievement in math always forget what teachers tell them to do and (b) know one way to help these students.</p> <p>In contrast to the extensive studies on typical children and aging PM performance (Einstein, McDaniel, & Scullin, 2012; Mahy & Moses, 2011; Mahy, Moses, & Kliegel, 2014; Scullin, Bugg, McDaniel, & Einstein, 2011; Uttl, 2011), only a couple of investigations have focused on low-achieving students (Dong, Zhou, & Guo, 2008; Ji, 2012). Both studies used the classical dual-task paradigm (Einstein & McDaniel, 1990), which includes ongoing tasks and PM tasks. Ji (2012) directed participants to remember two words and their color in the PM encoding phase. Results showed that high-achieving students outperformed low-achieving students in the event-based PM and were better at transferring between the PM task and an ongoing task. Dong et al. (2008) compared the effects of cognitive style and reminders on different kinds of PM between low-achieving children and average-achieving children. Results showed that the performance of low-achieving students was as good as that of average-achieving children in event-based PM tasks but not as good as that of average-achieving children in time-based PM tasks without reminders. The reminder facilitated the performance of low-achieving students in time-based PM tasks but did not improve their performance in event-based PM tasks. In the study by Dong et al., the tasks placed few working memory (WM) demands on low-achieving children.</p> <p>The present study raises the question whether low-achieving students would perform as well as relatively higher-achieving students on event-based PM if demands were made on WM; that is, does WM load interact on PM performance among low- and high-achieving students, and do reminders have a mediating role on performance? No study to date has addressed these questions. In the present study, both WM load of ongoing task and the use of a reminder were investigated with low- and high-achieving students in math.</p> <p>Studies have suggested that the use of external reminders benefits PM (Cartee, Fink, & Pak, 2013; Henry, Rendell, Phillips, Dunlop, & Kliegal, 2012; Maylor, 1996; McDaniel & Einstein, 1993). Actually, reminders improve PM performance only when they are distinctive, clear, and strongly associated to intention (McDaniel & Einstein, 1993) and when the ongoing task requires little cognitive resources (Einstein & McDaniel, 1990). In addition, some studies suggested that reminders are effective only when they refer to the PM target and the action to be carried out (Guynn, Einstein, & McDaniel, 1998; Maylor, 1996).</p> <p>On the basis of previous studies, we used a distinctive reminder in this experiment and hypothesized that the reminder would improve PM for all participants. In addition, we theorized that the effect of WM load increase would be most pronounced in low-achieving students. We also predicted an interaction between reminder and WM load conditions as a function of achievement group.</p> <hd id="AN0124638941-2">Method</hd> <p></p> <hd id="AN0124638941-3">Participants</hd> <p>Participants were selected from two middle schools (Grades 7-9) in Fuzhou, Fujian province, China. First, we obtained</p> <p>students' scores on their math academic achievement tests in the latest midterm and final examinations, which were compiled and administered by their teachers and involved the same two examinations per grade. According to some studies (Cai, Li, & Deng, 2013; B. Zhou, 2008; L. Zhou, 2012) -- and the teachers of the same grade -- students who scored >20th percentile in their grade were considered high-achieving students, and students who scored <20th percentile were considered low-achieving students. Further confirmation of high and low math-achieving status was confirmed by the child's classroom teacher, who was very familiar with the status of every student. Finally, 59 students were assigned to the high-achieving group and 54 to the low-achieving group. Their performances were in the normal range on standardized intelligence tests (Raven's Standard Progressive Matrices; China version revised by Zhang & Wang, 1989). The intelligence scores and demographic characteristics of each group of students are provided in Table 1. Informed consent was provided by their parents before the experiment.</p> <hd id="AN0124638941-4">Materials and Procedure</hd> <p>The stimuli were the 26 English-alphabet letters displayed in uppercase, measuring 15 X 10 mm. The letter "D" was used as a PM cue, and the others were used as n-back trials. A card with "D" written on it was put beside the computer for the reminder condition.</p> <p>To index PM, a classical dual-task paradigm was used (Einstein & McDaniel, 1990). Each condition involved dual tasks: the ongoing task and the event-based PM task (press "K" key at the event of letter "D"). Since the n-back task is now in widespread use as a measure of WM in experimental settings and allows for manipulation of WM systematically, an n-back task was used to create the WM load of an ongoing task in this experiment.</p> <p>A 2 X 2 X 2 mixed factorial design was used: Ability Group (high-achieving students, low-achieving students) X WM Load of Ongoing Task (1-back, 2-back) X Reminder (with reminder, no reminder). The reminder varied among participants, and the WM load of ongoing task varied within participants. Both high- and low-achieving students were assigned to each condition (reminder, no reminder). Intelligence scores were matched (t = -0.101, p > .05) between the with-reminder group (54.88 ± 3.82) and the no-reminder group (54.93 ± 3.97).</p> <p>There were 3 blocks in each condition (1 practice block of 100 trials and 2 test blocks of 100 trials each). Each block included 2 PM cues, 49 n-back targets, and 49 non-targets. Each stimulus was displayed for the maximum of 2,500 ms or until a response was made, followed by a blank with the stimulus-onset asynchrony at 3,000 ms; then, the letter for the next trial was presented (see Figure 1). In the ongoing tasks (n-back tasks), individuals were asked to report whether the letter currently presented matched the letter that had been presented as the n-back letter. Individuals were instructed to place their hands on the computer keyboard at the beginning of the task and press the "F" key if the current letter matched the n-back letter and the "J" key if the current letter was not an n-back match. Meanwhile, participants were also instructed that when the letter "D" appeared, they should respond by pressing the "K" key. For the 1-back condition, target trials represented the second letter of a repetition in the series of letters (e.g., "S R R"); for the 2-back condition, target trials represented the second letter of a repetition following one intervening letter (e.g., "L Q L"). For the 1- and 2-back conditions, nontarget trials were those that did not represent 1- or 2-back repetitions or PM cues. The high and low WM load conditions were counterbalanced across participants. The experiment was compiled by E-Prime 1.1 (Psychology Software Tools, Inc., Sharpsburg, Pennsylvania) and was presented on computer.</p> <hd id="AN0124638941-5">Analysis</hd> <p>SPSS 12.0 (IBM, Chicago, Illinois) was used for all statistical analyses.</p> <hd id="AN0124638941-6">Results</hd> <p></p> <hd id="AN0124638941-7">PM Performance</hd> <p>Mixed 2 X 2 X 2 (Ability Group X WM Load X Reminder) analysis of variance models were used to evaluate the accuracy (see Table 2) and reaction time (see Table 3) of the PM tasks. For accuracy, each main effect was significant: ability group, F(<reflink idref="bib1" id="ref1">1</reflink>, 109) = 8.23, p < .01, η[su[p 2] = .07. The accuracy of PM was lower for low-achieving students than for high-achieving students: WM load, F(<reflink idref="bib1" id="ref2">1</reflink>, 109) = 43.87, p < .001, η[su[p 2] = .29. The accuracy of PM was higher for the low WM load condition than for the high WM load condition: reminder, F(<reflink idref="bib1" id="ref3">1</reflink>, 109) = 112.76, p < .001, η[su[p 2] = .51. The accuracy of PM was higher for the with-reminder condition than the no-reminder condition. The interaction between WM load and reminder was significant, F(<reflink idref="bib1" id="ref4">1</reflink>, 109) = 10.97, p < .01, η[su[p 2] = .09.</p> <p>An independent sample t test was conducted to compare the reminder and no-reminder conditions in each WM load condition. The results showed that the reminder condition improved accuracy more in the 1-back condition, mean difference (MD) = 0.36, t(<reflink idref="bib1" id="ref5">1</reflink>, 111) = 8.62, p < .001, than in the 2-back condition, MD = 0.23, t(<reflink idref="bib1" id="ref6">1</reflink>, 111) = 7.77, p < .001. As shown in Figure 2, the reminder condition improved students' PM accuracy, especially in the low WM load condition.</p> <p>For the response time, each main effect was significant: ability group, F(<reflink idref="bib1" id="ref7">1</reflink>, 109) = 10.05, p < .01, η[su[p 2] = .08. The response time of PM was longer for low-achieving students than for high-achieving students: WM load, F(<reflink idref="bib1" id="ref8">1</reflink>, 109) = 49.73, p < .001, η[su[p 2] = .31. The response time of PM was shorter for the low WM load condition than for the high WM load condition: reminder, F(<reflink idref="bib1" id="ref9">1</reflink>, 109) = 59.74, p < .01, η[su[p 2] = .35. The response time of PM was shorter for the reminder condition than for the no-reminder condition; the interaction between WM load and the reminder condition was significant: F(<reflink idref="bib1" id="ref10">1</reflink>, 109) = 23.30, p < .001, η[su[p 2] = .18.</p> <p>A test of simple effects showed that no significant difference occurred between WM load conditions within the reminder condition, F(<reflink idref="bib1" id="ref11">1</reflink>, 111) = 1.72, p > .05, but within the no-reminder condition, there was a significant difference between the different WM load conditions, F(<reflink idref="bib1" id="ref12">1</reflink>, 111) = 58.88, p < .001. The response time for the PM task in the 1-back condition was significantly faster than that in the 2-back condition. These results suggest that the reminder conditions accelerated participants' PM response, especially in the high WM load condition (see Figure 3). The interaction between WM load and ability group was significant, F(<reflink idref="bib1" id="ref13">1</reflink>, 109) = 20.04, p < .001, η[su[p 2] = .16. A test of simple effects showed that for high-achieving students, no significant difference in response time occurred between the different WM load conditions, F(<reflink idref="bib1" id="ref14">1</reflink>, 111) = 2.75, p < .06. In contrast, for low-achieving students, the response time of PM in the 2-back condition was significantly slower than that in the 1-back condition, F(<reflink idref="bib1" id="ref15">1</reflink>, 111) = 54.79, p < .001. These results suggest that the influence of the high WM load was more pronounced for low-achieving students than for high-achieving students.</p> <hd id="AN0124638941-8">Ongoing Task Performance</hd> <p>Mixed 2 X 2 X 2 (Ability Group X WM Load X Reminder) analysis of variance models were used to evaluate the accuracy (see Table 4) and reaction time (see Table 5) of the ongoing tasks. For accuracy, the main effects were significant for ability group, F(<reflink idref="bib1" id="ref16">1</reflink>, 109) = 27.52, p < .001, η[su[p 2] = .20. The accuracy of ongoing tasks was lower for low-achieving students than for high-achieving students: WM load, F(<reflink idref="bib1" id="ref17">1</reflink>, 109) = 141.87, p < .001, η[su[p 2] = .57. The accuracy of ongoing tasks was higher for the low WM load condition than the high WM load condition: reminder condition, F(<reflink idref="bib1" id="ref18">1</reflink>, 109) = 105.53, p < .001, η[su[p 2] = .49. The accuracy of ongoing tasks was higher for the reminder condition than the no-reminder condition. The interaction between WM load and the reminder condition was significant, F(<reflink idref="bib1" id="ref19">1</reflink>, 109) = 10.74, p < .01, η[su[p 2] = .09.</p> <p>An independent sample t test was conducted to compare the reminder and no-reminder conditions in each WM load condition. The results showed that the accuracy in the no-reminder condition decreased more in the 2-back condition, MD = 0.16, t(<reflink idref="bib1" id="ref20">1</reflink>, 111) = 9.70, p < .001, than that in the 1-back condition, MD = 0.09, t(<reflink idref="bib1" id="ref21">1</reflink>, 111) = 5.28, p < .001. These findings suggest that performing PM had more interference on the ongoing task in the no-reminder conditions, especially within the 2-back condition.</p> <p>For the response time, each main effect was significant: ability group, F(<reflink idref="bib1" id="ref22">1</reflink>, 109) = 8.18, p < .01, η[su[p 2] = .07. The response time of ongoing tasks was longer for low-achieving students than for high-achieving students: WM load, F(<reflink idref="bib1" id="ref23">1</reflink>, 109) = 105.60, p < .001, η[su[p 2] = .49. The response time of ongoing tasks was shorter for the low WM load condition than for the high WM load condition: reminder, F(<reflink idref="bib1" id="ref24">1</reflink>, 109) = 63.88, p < .001, η[su[p 2] = .37. The</p> <p>response time of ongoing tasks was shorter for the reminder condition than the no-reminder condition. The interaction between WM load and the reminder condition was significant, F(<reflink idref="bib1" id="ref25">1</reflink>, 109) = 3.69, p < .06, η[su[p 2] = .03. A test of simple effects showed that significant differences occurred between the different reminder levels in both the 1-back condition, F(<reflink idref="bib1" id="ref26">1</reflink>, 111) = -7.58, p < .001, and the 2-back condition, F(<reflink idref="bib1" id="ref27">1</reflink>, 111) = -7.20, p < .001; with PM reminder versus no reminder, the reaction time was reduced more in the 2-back condition, 223 ms, t(<reflink idref="bib1" id="ref28">1</reflink>, 111) = -7.20, p < .001, than in the 1-back condition, 183 ms, t(<reflink idref="bib1" id="ref29">1</reflink>, 111) = -7.58, p < .001. This suggested that performing PM with a reminder might have less interference on the ongoing task than that without the reminder, especially in the higher WM load condition.</p> <p>The interaction between WM load and ability group was significant, F(<reflink idref="bib1" id="ref30">1</reflink>, 109) = 7.49, p < .01, η[su[p 2] = .06. A test of simple main effects showed that when WM load was low, no significant difference existed between high-and low-achieving students, F(<reflink idref="bib1" id="ref31">1</reflink>, 111) = 1.64, p > .05. In contrast, when the WM load was high, there was a significant difference between the high- and low-achieving students on the measure of response time, F(<reflink idref="bib1" id="ref32">1</reflink>, 111) = 2.89, p < .01. The response time for the 2-back task was significantly slower for low-achieving students than for high-achieving students.</p> <hd id="AN0124638941-9">Discussion</hd> <p></p> <hd id="AN0124638941-10">PM Performance</hd> <p>The present study provided some significant results. For one thing, all students performed better in the low WM load condition than in the high WM load condition, and the high WM load conditions had more influence on low-achieving students in math than on high-achieving students in math. As mentioned in the introduction, PM task and ongoing task competed for the limited cognitive resources, so when the WM load of ongoing task increased, PM performance decreased. Gathercole and Pickering (2000) investigated the association between WM ability and children's academic achievements, finding that (a) low-achieving students had central executive deficits and (b) complex WM skills were closely linked with children's academic progress within the early years of school. Mahy and Moses (2011) believed that executive functions -- which are involved in the initial encoding, maintenance, and retrieval of intentions -- have an important role in PM performance. Some researchers (Mahy et al., 2014) assessed the current state of research on children's PM and proposed an executive function framework for the development of PM according to the theory that different executive functions (e.g., WM, inhibition, set shifting, planning, and monitoring) play more important roles than others at certain stages of PM.</p> <p>The results also clearly showed that reminding students improved their PM accuracy, especially in the low WM load condition. The introduction of reminders further accelerated participants' PM response time, especially in the high WM load condition. Previous studies have suggested that reminders benefit PM performance when they are obvious and clear (McDaniel & Einstein, 1993) and when they refer to PM target and action to be performed (Maylor, 1996). Some studies indicated that successful PM performance will be maintained when paired with picture reminders rather than with text reminders (e.g., Cartee et al., 2013). In the present study, the reminder was a card with the PM target written on it and put obviously beside the computer, so it was distinctive enough to remind participants of the PM target and task. A study by Einstein and McDaniel (1990) indicated that a reminder was more effective when the ongoing task did not require heavy attentive resources. In the present study, use of a reminder improved students' PM accuracy, especially in the low WM load condition, because in that condition, a reminder released participants from monitoring and continuous heightened activation of intention in memory. In the high load condition, however, the ongoing task was so difficult that it occupied many resources, and participants could not be released. This result is consistent with the results of the study by Einstein and McDaniel. However, participants' PM response time was accelerated, especially in the high WM load condition. Perhaps the PM response time was too fast to be improved in the 1-back task but was slow and still had room to be improved in the 2-back task.</p> <hd id="AN0124638941-11">Ongoing Task Performance</hd> <p>In this study, the performances of ongoing tasks were compared between reminder and no-reminder conditions in each WM load condition. Results showed that performances in reminder conditions were better than those in the no-reminder conditions. PM research has found that having an intention interfered with ongoing activities (Lourenço & Maylor, 2014). In the present study, PM performances were facilitated by the use of a reminder; thus, they occupied less cognitive resources than those in the no-reminder condition, and task interferences on the ongoing task were lessened. Performance of the ongoing tasks all improved in the reminder conditions. Unexpectedly, the accuracy of an ongoing task increased more and the response time decreased more in the 2-back condition than in the 1-back condition with reminder. This might be due to the different difficulty of ongoing tasks. For the 1-back task, it was too easy even without a PM reminder. With the PM reminder, it improved to its highest level, which shows ceiling effects. For the 2-back task, however, it was very difficult without a PM reminder, so performance was far worse than in the 1-back task. Performance improved greatly with the PM reminder in the 2-back task, and it improved more than that in the 1-back condition due to the large difference between the two tasks without the PM reminder.</p> <p>Decreased performances of ongoing tasks were observed when WM load in the ongoing task was high, particularly for low-achieving students. The central executive is assumed to allocate resources between maintenance of PM intentions and ongoing tasks; also, it has been demonstrated that executive functions were involved in the n-back tasks (Chatham et al., 2011). As discussed before, low-achieving students had some deficit in executive functions, so high-achieving students outperformed low-achieving students in the high WM load tasks.</p> <p>From these results, we know that low-achieving students were weak at PM, and a reminder could help them with PM performance; therefore, low-achieving students should be trained how to set up reminders for their PM. They should learn to set up distinctive, clear reminders, and these reminders should refer to the PM target and action to be performed. In addition, a picture reminder was shown to be better than a text reminder. Examples include (a) drawing a picture of a butterfly and sticking it on a bookshelf to remind oneself to do science homework about research on butterflies and (b) drawing a picture of a key and sticking it on the door to remind oneself to bring the door key before going out. We also found that the deficit of WM in low-achieving students influenced their PM performance, so training of WM would help them with their PM performance. Teachers and parents should learn some measures to improve WM of low-achieving children. If low-achieving students and students with a learning disability do not forget what a teacher tells them to do or what to do when they meet a math problem, their academic achievement will improve.</p> <p>Our current knowledge about the influence of PM on low-achieving students and the underlying mechanisms remains limited. More research should focus on more influencing factors of PM on low-achieving students (e.g., task importance, characteristics of PM target, ways of encoding). It is also important to determine the underlying cognitive and neural mechanisms. More work should be done to find out how to help students improve their PM.</p> <hd id="AN0124638941-12">Conclusions</hd> <p>As expected, reminding children does improve PM performance. High-achieving students outperformed low-achieving students on PM and n-back tasks in this experiment. However, as WM load increases, the influence on PM is more pronounced on low-achieving students than high-achieving students.</p> <hd id="AN0124638941-13">Acknowledgments</hd> <p>We are grateful to the teachers, parents, and students who gave their time to participate in the study.</p> <hd id="AN0124638941-14">Declaration of Conflicting Interests</hd> <p>The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.</p> <hd id="AN0124638941-15">Funding</hd> <p>The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by a grant from the Education Ministry of China (12YJA190002).</p> <hd id="AN0124638941-16">Table 1. Intelligence Score and Demographic Characteristics of Two Ability Groups</hd> <p> <ephtml> <div class="table-size-normal table-border"><table border="1"> <tr> <td>Characteristics/scores</td> <td>High-achieving students</td> <td>Low-achieving students</td> </tr> <tr> <td>Students, n</td> <td></td> <td></td> </tr> <tr> <td>Male</td> <td>27</td> <td>31</td> </tr> <tr> <td>Female</td> <td>32</td> <td>23</td> </tr> <tr> <td>Total</td> <td>59</td> <td>54</td> </tr> <tr> <td>Age, years</td> <td></td> <td></td> </tr> <tr> <td>M</td> <td>13.61</td> <td>13.37</td> </tr> <tr> <td>SD</td> <td>1.86</td> <td>1.79</td> </tr> <tr> <td>Intelligence score</td> <td></td> <td></td> </tr> <tr> <td>M</td> <td>57.05</td> <td>52.56</td> </tr> <tr> <td>SD</td> <td>3.72</td> <td>3.89</td> </tr> </table></div> </ephtml> </p> <hd id="AN0124638941-17">Table 2. Accuracy of Prospective Memory by Working Memory Load and Reminder Condition</hd> <p> <ephtml> <div class="table-size-normal table-border"><table border="1"> <tr> <td></td> <td></td> <td>Reminder</td> <td></td> <td></td> <td></td> <td>No reminder</td> <td></td> <td></td> </tr> <tr> <td></td> <td>HA (n = 30)</td> <td></td> <td>LA (n = 26)</td> <td></td> <td>HA (n = 29)</td> <td></td> <td>LA (n = 28)</td> <td></td> </tr> <tr> <td>Cognitive demand</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> </tr> <tr> <td>1-back</td> <td>.96</td> <td>.10</td> <td>.90</td> <td>.16</td> <td>.57</td> <td>.34</td> <td>.53</td> <td>.28</td> </tr> <tr> <td>2-back</td> <td>.75</td> <td>.08</td> <td>.65</td> <td>.15</td> <td>.53</td> <td>.15</td> <td>.41</td> <td>.20</td> </tr> </table></div> </ephtml> </p> <p>Note. HA = high-achieving students; LA = low-achieving students.</p> <hd id="AN0124638941-18">Table 3. Response Time (ms) of Prospective Memory by Working Memory Load and Reminder Condition</hd> <p> <ephtml> <div class="table-size-normal table-border"><table border="1"> <tr> <td></td> <td>Reminder</td> <td></td> <td></td> <td></td> <td>No reminder</td> <td></td> <td></td> <td></td> </tr> <tr> <td></td> <td>HA (n = 30)</td> <td></td> <td>LA (n = 26)</td> <td></td> <td>HA (n = 29)</td> <td></td> <td>LA (n = 28)</td> <td></td> </tr> <tr> <td>Cognitive demand</td> <td>SD</td> <td>M</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> </tr> <tr> <td>1-back</td> <td>562</td> <td>78</td> <td>644</td> <td>127</td> <td>766</td> <td>136</td> <td>773</td> <td>117</td> </tr> <tr> <td>2-back</td> <td>557</td> <td>106</td> <td>691</td> <td>157</td> <td>819</td> <td>189</td> <td>943</td> <td>169</td> </tr> </table></div> </ephtml> </p> <p>Note. HA = high-achieving students; LA = low-achieving students.</p> <hd id="AN0124638941-19">Table 4. Accuracy of Ongoing Task by Working Memory Load and Reminder Condition</hd> <p> <ephtml> <div class="table-size-normal table-border"><table border="1"> <tr> <td></td> <td>Reminder</td> <td></td> <td></td> <td></td> <td>No reminder</td> <td></td> <td></td> <td></td> </tr> <tr> <td></td> <td>HA (n = 30)</td> <td></td> <td>LA (n = 26)</td> <td></td> <td>HA (n = 29)</td> <td></td> <td>LA (n = 28)</td> <td></td> </tr> <tr> <td>Cognitive demand 1-back</td> <td>M .96</td> <td>SD .10</td> <td>M .94</td> <td>SD .03</td> <td>M .89</td> <td>SD .09</td> <td>M .82</td> <td>SD .16</td> </tr> <tr> <td>2-back</td> <td>.90</td> <td>.08</td> <td>.82</td> <td>.08</td> <td>.74</td> <td>.08</td> <td>.66</td> <td>.08</td> </tr> </table></div> </ephtml> </p> <p>Note. HA = high-achieving students; LA = low-achieving students.</p> <hd id="AN0124638941-20">Table 5. Response Time (ms) of Ongoing Task by Working Memory Load and Reminder Condition</hd> <p> <ephtml> <div class="table-size-normal table-border"><table border="1"> <tr> <td></td> <td>Reminder</td> <td></td> <td></td> <td></td> <td>No reminder</td> <td></td> <td></td> <td></td> </tr> <tr> <td></td> <td>HA (n = 30)</td> <td></td> <td>LA (n = 26)</td> <td></td> <td>HA (n = 29)</td> <td></td> <td>LA (n = 28)</td> <td></td> </tr> <tr> <td>Cognitive demand</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> <td>M</td> <td>SD</td> </tr> <tr> <td>1-back</td> <td>458</td> <td>87</td> <td>534</td> <td>151</td> <td>671</td> <td>123</td> <td>683</td> <td>141</td> </tr> <tr> <td>2-back</td> <td>519</td> <td>128</td> <td>641</td> <td>179</td> <td>763</td> <td>153</td> <td>838</td> <td>129</td> </tr> </table></div> </ephtml> </p> <p>Note. HA = high-achieving students; LA = low-achieving students.</p> <p>Figure 1. Letter-by-letter presentation of ongoing n-back task and embedded prospective memory task.</p> <p>Figure 2. The accuracy of prospective memory (PM) for high-achieving (HA) and low-achieving (LA) students in the reminder and without-reminder conditions.</p> <p>Figure 3. The response time of prospective memory (PM) for high-achieving (HA) and low-achieving (LA) students in the reminder and without-reminder conditions.</p> <hd id="AN0124638941-21">References</hd> <p>Cai, D., Li, Q., & Deng, C. (2013). Working memory features of low-achieving students in math: Domain general or domain specific? Acta Psychologica Sinica, 45(<reflink idref="bib2" id="ref33">2</reflink>), 193-205.</p> <p>Cartee, N., Fink, N., & Pak, R. (2013). The effects of reminder type and anticipatory interval on prospective memory. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 57, 1750-1754.</p> <p>Chatham, C. H., Herd, S. A., Brant, A. M., Hazy, T. E., Miyake, A., O'Reilly, R., & Friedman, N. 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  Data: Working Memory Load and Reminder Effect on Event-Based Prospective Memory of High- and Low-Achieving Students in Math
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Youzhen%22">Chen, Youzhen</searchLink><br /><searchLink fieldCode="AR" term="%22Lian%2C+Rong%22">Lian, Rong</searchLink><br /><searchLink fieldCode="AR" term="%22Yang%2C+Lixian%22">Yang, Lixian</searchLink><br /><searchLink fieldCode="AR" term="%22Liu%2C+Jianrong%22">Liu, Jianrong</searchLink><br /><searchLink fieldCode="AR" term="%22Meng%2C+Yingfang%22">Meng, Yingfang</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Learning+Disabilities%22"><i>Journal of Learning Disabilities</i></searchLink>. Sep-Oct 2017 50(5):602-608.
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  Data: SAGE Publications and Hammill Institute on Disabilities. 2455 Teller Road, Thousand Oaks, CA 91320. Tel: 800-818-7243; Tel: 805-499-9774; Fax: 800-583-2665; e-mail: journals@sagepub.com; Web site: http://sagepub.com
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  Data: 7
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  Data: <searchLink fieldCode="DE" term="%22Short+Term+Memory%22">Short Term Memory</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+Processes%22">Cognitive Processes</searchLink><br /><searchLink fieldCode="DE" term="%22Low+Achievement%22">Low Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22High+Achievement%22">High Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematics+Achievement%22">Mathematics Achievement</searchLink><br /><searchLink fieldCode="DE" term="%22Middle+School+Students%22">Middle School Students</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Intelligence+Tests%22">Intelligence Tests</searchLink><br /><searchLink fieldCode="DE" term="%22Visual+Stimuli%22">Visual Stimuli</searchLink>
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  Data: 10.1177/0022219416668322
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  Data: 0022-2194
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  Data: The effects of working memory (WM) demand and reminders on an event-based prospective memory (PM) task were compared between students with low and high achievement in math. WM load (1- and 2-back tasks) was manipulated as a within-subject factor and reminder (with or without reminder) as a between-subject factor. Results showed that high-achieving students outperformed low-achieving students on all PM and n-back tasks. Use of a reminder improved PM performance and thus reduced prospective interference; the performance of ongoing tasks also improved for all students. Both PM and n-back performances in low WM load were better than in high WM load. High WM load had more influence on low-achieving students than on high-achieving students. Results suggest that low-achieving students in math were weak at PM and influenced more by high WM load. Thus, it is important to train these students to set up an obvious reminder for their PM and improve their WM.
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        PageCount: 7
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      – SubjectFull: Low Achievement
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      – TitleFull: Working Memory Load and Reminder Effect on Event-Based Prospective Memory of High- and Low-Achieving Students in Math
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