Search

People can use different internal strategies to manage their daily tasks, but systematic research on these strategies and their significance for actual performance is still quite sparse. Here we examined self-reported internal strategy use with a 10-block version of the videogame EPELI (Executive Performance in Everyday LIving) in a group of 202 neurotypical adults of 18-50 years of age. In the game, participants perform lists of everyday tasks from memory while navigating in a virtual apartment. Open-ended strategy reports were collected after each EPELI task block, and for comparison also after an EPELI Instruction Recall task and a Word List Learning task assessing episodic memory. On average, 45% of the participants reported using some strategy in EPELI, the most common types being grouping (e.g., performing the tasks room by room), utilising a familiar action schema, and condensing information (e.g., memorising only keywords). Our pre-registered hypothesis on the beneficial effect of self-initiated strategy use gained support, as strategy users showed better performance on EPELI as compared with no strategy users. One of the strategies, grouping, was identified as a clearly effective strategy type. Block-by-block transitions suggested gradual stabilisation of strategy use over the 10 EPELI blocks. The proneness to use strategies showed a weak but reliable association between EPELI and Word List Learning. Overall, the present results highlight the importance of internal strategy use for understanding individual differences in memory performance, as well as the potential benefit for internal strategy employment when faced with everyday memory tasks.

Working memory (WM) training, typically entailing repetitive practice with one or two tasks, has mostly yielded only limited task-specific transfer effects. We developed and tested a new WM training approach where the task paradigm, stimulus type, and predictability of the stimulus sequence were constantly altered during the 4-week training period. We expected that this varied training protocol would generate more extensive transfer by facilitating the use of more general strategies that could be applied to a range of WM tasks. Pre-post transfer effects following varied training (VT group, n = 60) were compared against traditional training (TT group, training a single adaptive WM task, n = 63), and active controls (AC, n = 65). As expected, TT evidenced strong task-specific near transfer as compared to AC. In turn, VT exhibited task-specific near transfer only on one of the measures, and only as compared to the TT group. Critically, no evidence for task-general near transfer or far transfer effects was observed. In sum, the present form of VT failed to demonstrate broader transfer. Nevertheless, as VT has met with success in other cognitive domains, future studies should probe if and how it would be possible to design WM training protocols that promote structural learning where common features of specific tasks would be identified and utilised when selecting strategies for novel memory tasks.

Cognitive task performance is a dynamic process that evolves over time, starting from the first encounters with a task. An important aspect of these task dynamics is the employment of strategies to support successful performance and task acquisition. Focusing on episodic memory performance, we: (1) tested two hypotheses on the effects of novelty and task difficulty on strategy use, (2) replicated our previous results regarding strategy use in a novel memory task, and (3) evaluated whether repeated open-ended strategy queries affect task performance and/or strategy use. The present pre-registered online study comprised 161 adult participants who were recruited through the Prolific crowdsourcing platform. We employed two separate 5-block list learning tasks, one with 10 pseudowords and the other with 18 common nouns, and collected recall performance and strategy reports for each block. Using Bayesian linear mixed effects models, the present findings (1) provide some support for the hypothesis that task-initial strategy development is not triggered only by task novelty, but can appear also in a familiar, moderately demanding task; (2) replicate earlier findings from an adaptive working memory task indicating strategy use from the beginning of a task, associations between strategy use and objective task performance, and only modest agreement between open-ended versus list-based strategy reports; and (3) indicate that repeated open-ended strategy reports do not affect objective recall. We conclude that strategy use is an important aspect of memory performance right from the start of a task, and it undergoes development at the initial stages depending on task characteristics. In a larger perspective, the present results concur with the views of skill learning and adaptivity in cognitive task performance.

Increasing evidence indicates that the coronavirus disease 2019 (COVID-19) pandemic is associated with adverse psychological effects, including heightened levels of anxiety. This study examined whether COVID-19-related anxiety levels during the early stage of the pandemic predicted demanding working memory (WM) updating performance. Altogether, 201 healthy adults (age range, 18-50) mostly from North America and the British Isles were recruited to this study via the crowdsourcing site . The results showed that higher levels of COVID-19-related anxiety during the first weeks of the pandemic outbreak were associated with poorer WM performance as measured by the n-back paradigm. Critically, the unique role of COVID-19-related anxiety on WM could not be explained by demographic factors, or other psychological factors such as state and trait anxiety or fluid intelligence. Moreover, across three assessment points spanning 5-6 weeks, COVID-19-related anxiety levels tended to decrease over time. This pattern of results may reflect an initial psychological "shock wave" of the pandemic, the cognitive effects of which may linger for some time, albeit the initial anxiety associated with the pandemic would change with habituation and increasing information. Our results contribute to the understanding of cognitive-affective reactions to a major disaster.

Online quizzes building upon the principles of retrieval practice can have beneficial effects on learning, especially long-term retention. However, it is unexplored how interindividual differences in relevant background characteristics relate to retrieval practice activities in e-learning. Thus, this study sought to probe for this research question on a massive open online course (MOOC) platform where students have the optional possibility to quiz themselves on the to-be-learned materials. Altogether 105 students were assessed with a cognitive task tapping on reasoning, and two self-assessed personality measures capturing need for cognition (NFC), and grittiness (GRIT-S). Between-group analyses revealed that cognitively high performing individuals were more likely to use the optional quizzes on the platform. Moreover, within-group analyses (n = 56) including those students using the optional quizzes on the platform showed that reasoning significantly predicted quiz performance, and quiz processing speed. NFC and GRIT-S were unrelated to each of the aforementioned retrieval practice activities.

Cognitive mechanisms underlying the limited transfer effects of working memory (WM) training remain poorly understood. We tested in detail the Strategy Mediation hypothesis, according to which WM training generates task-specific strategies that facilitate performance on the trained task and its untrained variants. This large-scale pre-registered randomized controlled trial (n = 258) used a 4-week adaptive WM training with a single digit n-back task. Strategy use was probed with open-ended strategy reports. We employed a Strategy training group (n = 73) receiving external strategy instruction, a Traditional training group (n = 118) practicing without strategy instruction, and Passive controls (n = 67). Both training groups showed emerging transfer to untrained n-back task variants already at intermediate test after 3 training sessions, extending to all untrained n-back task variants at posttest after 12 training sessions. The Strategy training group outperformed the Traditional training group only at the beginning of training, indicating short-lived strategy manipulation effects. Importantly, in the Traditional training group, strategy evolvement modulated the gains in the trained and untrained n -back tasks, supporting the Strategy Mediation hypothesis. Our results concur with the view of WM training as cognitive skill learning.

Working memory (WM) training with the N-Back task has been argued to improve cognitive capacity and general cognitive abilities (the Capacity Hypothesis of training), although several studies have shown little or no evidence for such improvements beyond tasks that are very similar to the trained task. Laine et al. demonstrated that instructing young adult participants to use a specific visualisation strategy for N-back training resulted in clear, generalised benefits from only 30 min of training (Strategy Mediation Hypothesis of training). Here, we report a systematic replication and extension of the Laine et al. study, by administering 60 younger and 60 older participants a set of WM tasks before and after a 30-min N-back training session. Half the participants were instructed to use a visualisation strategy, the others received no instruction. The pre-post test battery encompassed a criterion task (digit N-back), two untrained tasks N-back tasks (letters and colours), and three structurally different WM tasks. The instructed visualisation strategy significantly boosted at least some measures of N-back performance in participants of both age groups, although the strategy generally appeared more difficult to implement and less beneficial for older adults. However, the strategy did not improve performance on structurally different WM tasks. We also found significant associations between N-back performance and the type and level of detail of self-generated strategies in the uninstructed participants, as well as age group differences in reported strategy types. WM performance appeared to partly reflect the application of strategies, and Strategy Mediation should be considered to understand the mechanisms of WM training. Claims of efficient training should demonstrate useful improvement beyond task-specific strategies.

E-learning is being considered as a widely recognized option to traditional learning environments, allowing for highly tailor-made adaptive learning paths with the goal to maximize learning outcomes. However, for being able to create personalized e-learning systems, it is important to identify relevant student prerequisites that are related learning success. One aspect crucial for all kind of learning that is relatively unstudied in relation to e-learning is working memory (WM), conceptualized as the ability to maintain and manipulate incoming information before it decays. The aim of the present study was to examine how individual differences in online activities is related to visuospatial- and verbal WM performance. Our sample consisted of 98 participants studying on an e-learning platform. We extracted 18 relevant features of online activities tapping on Quiz accuracy, Study activity, Within-session activity, and Repetitive behavior. Using best subset multiple regression analyses, the results showed that individual differences in online activities significantly predicted verbal WM performance (p < 0.001, R2Adjusted = 0.166), but not visuospatial WM performance (p = 0.058, R2Adjusted= 0.065). The obtained results contribute to the existing research of WM in e-learning environments, and further suggest that individual differences in verbal WM performance can be predicted by how students interact on e-learning platforms.

Cognitive pre-requisites should be taken into consideration when providing personalized and adaptive digital content in web-based learning platforms. In order to achieve this it should be possible to extract these cognitive characteristics based on students´ study behavior. Working memory capacity (WMC) is one of the cognitive characteristics that affect students’ performance and their academic achievements. However, traditional approaches to measuring WMC are cognitively demanding and time consuming. In order to simplify these measures, Chang et al. (2015) proposed an approach that can automatically identify students’ WMC based on their study behavior patterns. The intriguing question is then whether there are study behavior characteristics that correspond to the students’ WMC? This work explores to what extent it is possible to map individual WMC data onto individual patterns of learning by correlating working memory capacity with learners´ study behavior in an adaptive web-based learning system. Several machine learning models together with a rich context model have been applied to identify the most relevant study behavior characteristics and to predict students’ WMC. The evaluation was performed based on data collected from 122 students during a period of 2 years using a web-based learning platform. The initial results show that there is no linear correlation with learners´ study behavior and their WMC.