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Raw data associated with manuscript "Deferred feedback does not dissociate implicit and explicit category learning systems: Commentary on Smith et al. (2014)"

Educational games have the potential to be innovative forms of learning assessment, by allowing us to not just study their knowledge but the process that takes students to that knowledge. This paper examines the mediating role of players' moves in digital games on changes in their pre-post classroom measures of implicit science learning. We applied automated detectors of strategic moves, built and validated from game log data combined with coded videos of gameplay of 69 students, to a new and larger sample of gameplay data. These data were collected as part of national implementation study of the physical science game, "Impulse". This study compared 213 students in 21 classrooms that only played the game and 180 students in 18 classrooms in where the players' teacher used game examples to bridge the implicit science learning in the game with explicit science content covered in class. We analyzed how learning outcomes between conditions were associated with six strategic moves students made during gameplay. Three of the strategic moves observed are consistent with an implicit understanding of Newton's First Law, the other three strategic moves were not. Path analyses suggest the mediating role of strategic moves on students' implicit science learning is different between the two conditions. [For complete proceedings, see ED560503.]

Educational games have the potential to be innovative forms of learning assessment, by allowing us to not just study their knowledge but the process that takes students to that knowledge. This paper examines the mediating role of players' moves in digital games on changes in their pre-post classroom measures of implicit science learning. We applied automated detectors of strategic moves, built and validated from game log data combined with coded videos of gameplay of 69 students, to a new and larger sample of gameplay data. These data were collected as part of national implementation study of the physical science game, "Impulse". This study compared 213 students in 21 classrooms that only played the game and 180 students in 18 classrooms in where the players' teacher used game examples to bridge the implicit science learning in the game with explicit science content covered in class. We analyzed how learning outcomes between conditions were associated with six strategic moves students made during gameplay. Three of the strategic moves observed are consistent with an implicit understanding of Newton's First Law, the other three strategic moves were not. Path analyses suggest the mediating role of strategic moves on students' implicit science learning is different between the two conditions. [For complete proceedings, see ED560503.]

Educational games have the potential to be innovative forms of learning assessment, by allowing us to not just study their knowledge but the process that takes students to that knowledge. This paper examines the mediating role of players' moves in digital games on changes in their pre-post classroom measures of implicit science learning. We applied automated detectors of strategic moves, built and validated from game log data combined with coded videos of gameplay of 69 students, to a new and larger sample of gameplay data. These data were collected as part of national implementation study of the physical science game, "Impulse". This study compared 213 students in 21 classrooms that only played the game and 180 students in 18 classrooms in where the players' teacher used game examples to bridge the implicit science learning in the game with explicit science content covered in class. We analyzed how learning outcomes between conditions were associated with six strategic moves students made during gameplay. Three of the strategic moves observed are consistent with an implicit understanding of Newton's First Law, the other three strategic moves were not. Path analyses suggest the mediating role of strategic moves on students' implicit science learning is different between the two conditions. [For complete proceedings, see ED560503.]

Educational games have the potential to be innovative forms of learning assessment, by allowing us to not just study their knowledge but the process that takes students to that knowledge. This paper examines the mediating role of players' moves in digital games on changes in their pre-post classroom measures of implicit science learning. We applied automated detectors of strategic moves, built and validated from game log data combined with coded videos of gameplay of 69 students, to a new and larger sample of gameplay data. These data were collected as part of national implementation study of the physical science game, "Impulse". This study compared 213 students in 21 classrooms that only played the game and 180 students in 18 classrooms in where the players' teacher used game examples to bridge the implicit science learning in the game with explicit science content covered in class. We analyzed how learning outcomes between conditions were associated with six strategic moves students made during gameplay. Three of the strategic moves observed are consistent with an implicit understanding of Newton's First Law, the other three strategic moves were not. Path analyses suggest the mediating role of strategic moves on students' implicit science learning is different between the two conditions. [For complete proceedings, see ED560503.]

Study exploring the impact of different instructional contexts on learning a symbolic math task.

Following results of the first preregistration in this project (Dynamic Development of Intuitions and Explicit Knowledge During Implicit Learning Paradigm), this preregistration describes a planned follow-up study intended to focus specifically on the extent to which individual differences in implicit learning are associated with timing and accuracy of intuitions. Results from Study 1 indicated that intuitions emerged from implicit learning experiences. We also found that intuitions preceded the development of explicit knowledge, and that explicit knowledge was related to the timing and accuracy of the intuitions. Together, these findings provide clear evidence in favor of hypotheses 1 and 3 (as indicated in Study 1 preregistration). We did not, however, find that stronger implicit learners developed intuitions more quickly, thereby failing to provide support for hypothesis 2. This pathway (i.e., implicit learning -> intuitions) is the focus of the present preregistration. In Study 1, participants were asked to indicate when they developed both intuitions and explicit knowledge of the SRTT learning blocks. This design allowed us to empirically test whether intuitions preceded explicit knowledge. Because we have now adequately demonstrated that intuitions precede – and may predict – the extent of one’s explicit knowledge, participants in Study 2 will be only asked to report intuitions. We anticipate that these new instructions will reduce cognitive load, perhaps allowing for comparatively fewer top-down influences on implicit learning.

This study aims to investigate the effect of statistical learning on re-enterant visual processing, assessed by the object substitution masking effect.

In this study, we seek to combine both psychological and physiological measures to try and understand the implicit motivation for experiencing different types of stimuli. More specifically, we are interested in how motivation to experience positive vs. negative stimuli differs and whether our metric of measuring motivation correlates with other implicit measures of motivation.

The study’s goal is to study auditory and visual statistical language learning in adult university students. The present work will examine statistical learning using a task developed by Batterink, Reber, Neville, and Paller (2015). This task assesses both implicit learning via a syllable monitoring task, and explicit learning via forced choice post-test. In addition, we will also be using a visual sequence learning task (serial reaction time task) to determine whether participants perform similarly on statistical learning regardless of sensory modality.

Over the last half century, mathematics education has seen numerous reform initiatives and standards. About every ten years, a new wave of documents offers recommendations on how to best teach mathematics. The Common Core State Standards for Mathematics (CCSSM; National Governors Association Center for Best Practices & Council of Chief State School Officers, 2010) builds on the concept of learning trajectories (LT) (Daro, Mosher, & Corcoran, 2011) and outlines the mathematics content and practices to be addressed at particular grade levels. With the widespread adoption of these standards, mathematics teacher educators have worked to share ideas about trajectories with teachers. Because research on learning largely developed separately from research on teaching, the authors' work used LTs to link these two bodies of research. They theorized the concept of Learning Trajectories Based Instruction (LTBI) as a model of teaching where instructional decisions are grounded in research on student learning in the form of trajectories and they interpreted several highly developed domains of research on mathematics teaching in relation to these trajectories (Sztajn, Confrey, Wilson, & Edgington, 2012). Since that time, the authors have worked to share this model with teachers in professional development settings, and their research has empirically examined and elaborated the affordances of LTBI. In this commentary, they critically analyze the LTBI model using Gutiérrez's (2007) dimensions of equity as a comprehensive framework for equity in mathematics education. Through this theoretical examination, they make explicit the assumptions inherent in the initial model and identify opportunities for LTBI to enhance equitable mathematics instruction. First, they briefly introduce current research on LTs and highlight principles of LTs that they contend are aligned with equitable instruction. Next, they present Gutiérrez's framework and a rationale for its selection as a tool for their theoretical analysis, briefly describing each of its dimensions. They detail their analysis of LTBI and conjecture what equity-oriented uses of the model might look like in instruction. The authors conclude with an invitation to the mathematics teacher education community to discuss the potentials and challenges of using LTs to support equitable mathematics instruction.

To succeed in STEM, students need to learn to use visual representations. Most prior research has focused on conceptual knowledge about visual representations that is acquired via verbally mediated forms of learning. However, students also need perceptual fluency: the ability to rapidly and effortlessly translate among representations. Perceptual fluency is acquired via nonverbal, implicit learning processes. A challenge for instructional interventions that focus on implicit learning is to model students' knowledge acquisition. Because implicit learning is non-verbal, we cannot rely on traditional methods, such as expert interviews or student think-alouds. This paper uses similarity learning, a machine learning method that can assess how people perceive similarity between visual representations. We used this approach to model how undergraduate students perceive similarity between visual representations of chemical molecules. The approach achieved good accuracy in predicting students' similarity judgments and expands expert predictions of how students might perceive visual representations of molecules. [For the full proceedings, see ED592609.]

Teacher immediacy has surfaced as an important instructional communication variable, yet little is known about how it functions to effect learning. To offer an explanation as to how teacher immediacy facilitates learning, a study investigated implicit communication theory. Subjects consisted of 625 undergraduate students who completed questionnaires later subjected to regression analyses. As in previous research, teacher verbal and nonverbal immediacy effected cognitive and affective learning. Findings indicate that implicit communication theory helps explain why learning occurs. Specifically, the dimensions of pleasure and arousal accounted for over half of learning variance. Further, implicit communication theory is significantly related to teacher immediacy. Results suggest that the integration of implicit communication theory with learning in general and specific instructional variables such as teacher immediacy is appropriate and fruitful. (Nine tables of data are included; 103 references are attached.) (Author)

Teacher immediacy has surfaced as an important instructional communication variable, yet little is known about how it functions to effect learning. To offer an explanation as to how teacher immediacy facilitates learning, a study investigated implicit communication theory. Subjects consisted of 625 undergraduate students who completed questionnaires later subjected to regression analyses. As in previous research, teacher verbal and nonverbal immediacy effected cognitive and affective learning. Findings indicate that implicit communication theory helps explain why learning occurs. Specifically, the dimensions of pleasure and arousal accounted for over half of learning variance. Further, implicit communication theory is significantly related to teacher immediacy. Results suggest that the integration of implicit communication theory with learning in general and specific instructional variables such as teacher immediacy is appropriate and fruitful. (Nine tables of data are included; 103 references are attached.) (Author)

Teacher immediacy has surfaced as an important instructional communication variable, yet little is known about how it functions to effect learning. To offer an explanation as to how teacher immediacy facilitates learning, a study investigated implicit communication theory. Subjects consisted of 625 undergraduate students who completed questionnaires later subjected to regression analyses. As in previous research, teacher verbal and nonverbal immediacy effected cognitive and affective learning. Findings indicate that implicit communication theory helps explain why learning occurs. Specifically, the dimensions of pleasure and arousal accounted for over half of learning variance. Further, implicit communication theory is significantly related to teacher immediacy. Results suggest that the integration of implicit communication theory with learning in general and specific instructional variables such as teacher immediacy is appropriate and fruitful. (Nine tables of data are included; 103 references are attached.) (Author)

We provide a sound and consistent foundation for the use of \emph{nonrandom} exploration data in "contextual bandit" or "partially labeled" settings where only the value of a chosen action is learned. The primary challenge in a variety of settings is that the exploration policy, in which "offline" data is logged, is not explicitly known. Prior solutions here require either control of the actions during the learning process, recorded random exploration, or actions chosen obliviously in a repeated manner. The techniques reported here lift these restrictions, allowing the learning of a policy for choosing actions given features from historical data where no randomization occurred or was logged. We empirically verify our solution on two reasonably sized sets of real-world data obtained from Yahoo!.

This systematic review will explore the following question: For late talkers and preschool children (i.e., 1;6-6;11) with Developmental Language Disorder/ Specific Language Impairment, is implicit vocabulary intervention associated with gains in receptive and expressive vocabulary, compared with other non-implicit vocabulary interventions or no intervention?

User preferences for items can be inferred from either explicit feedback, such as item ratings, or implicit feedback, such as rental histories. Research in collaborative filtering has concentrated on explicit feedback, resulting in the development of accurate and scalable models. However, since explicit feedback is often difficult to collect it is important to develop effective models that take advantage of the more widely available implicit feedback. We introduce a probabilistic approach to collaborative filtering with implicit feedback based on modelling the user's item selection process. In the interests of scalability, we restrict our attention to tree-structured distributions over items and develop a principled and efficient algorithm for learning item trees from data. We also identify a problem with a widely used protocol for evaluating implicit feedback models and propose a way of addressing it using a small quantity of explicit feedback data.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract We introduced haptic cues to the serial reaction time (SRT) sequence learning task alongside the standard visual cues to assess the relative contributions of visual and haptic stimuli to the formation of motor and perceptual memories. We used motorized keys to deliver brief pulse-like displacements to the resting fingers, expecting that the proximity and similarity of these cues to the subsequent response motor actions (finger-activated key-presses) would strengthen the motor memory trace in particular. We adopted the experimental protocol developed by Willingham (1999) to explore whether haptic cues contribute differently than visual cues to the balance of motor and perceptual learning. We found that sequence learning occurs with haptic stimuli as well as with visual stimuli and we found that irrespective of the stimuli (visual or haptic) the SRT task leads to a greater amount of motor learning than perceptual learning.

In many African countries, English is the medium of instruction in higher education even though students may not always be entirely familiar with "standard" English. This study aimed at investigating the relevance of English language competencies for teaching and learning from the perspective of students and lecturers. The study was carried out in Namibia and guided by the conceptual framework of implicit theories. Through a self-administered questionnaire, data were collected from a sample of 286 undergraduate students and 34 lecturers. Students and lecturers differed statistically significantly in all their views on the topic under investigation. While most of the lecturers (85.3%) believed that their students would not have good English language competencies, the majority of students (87.8%) rated their English between good and excellent. Most lecturers believed that insufficient English language competencies would cause a variety of problems for students such as having difficulty expressing themselves in English, following lectures, taking good notes during lectures, understanding academic texts, and writing coherent essays; in contrast, the majority of students believed that they had no such problems. The results are discussed with regard to practical implications for teaching and learning in higher education.

In a pre-registered experiment (https://doi.org/10.17605/OSF.IO/3D6H8) we tested whether meaningful actions drive implicit learning of temporal regularities. In the experiment, participants responded to targets that could randomly appear in three colors at three locations. They responded by pressing color-coded buttons with different fingers, thereby directly relating each color to a specific action. In half of the blocks one color (and thereby action) occurred regularly (i.e., every 3s), in the other half targets at one location occurred regularly. All other targets appeared at random moments. Results showed no behavioral benefits of either temporal regularity (i.e., neither in the regular action, nor in the regular location condition). This would be in line with one of our predictions: A correspondence between action and location is a prerequisite for learning temporal regularities. However, this null-findings could also be explained by (1) the color-response key-mapping being too difficult (i.e., there may be an additional, cognitive translation step from the color seen on screen to which finger to move/button to press); (2) the paradigm being too easy (i.e., learning the temporal regularity is not necessary in order to improve performance); or (3) Simon effects covering up effects of implicit learning (in Experiment 1 'fast' congruent responses (e.g., left key - left target) are interleaved with 'slow' incongruent responses (e.g., left key - right target) . To test these alternative explanations, we will modify our previous experimental design in the current study, such that the action and location regularity will be coupled. This design will also be in line with the outcome of our previous experiment (Salet et al. 2021; a correspondence between action and location is a prerequisite for learning temporal regularities). Throughout the experiment, each target location will be associated with one of three colors, and the color-mapped response keys will additionally be location-mapped (left key for the leftmost target, right key for the rightmost target, middle key for the middle-top target). This way, regular targets will have both a location- and action-regularity (location = action blocks), addressing explanation (1). With this setup, we will also avoid Simon interference, as the response-key is always congruent with the target location, addressing explanation (3). After this block, participants complete two additional blocks, in which we further attempt to disentangle the contribution of action- and location-regularity to implicit learning of temporal regularities. In the present design, we sought to do so without introducing strong Simon interference. Therefore, we present all three targets vertically in these blocks, aligned in the horizontal center of the screen. We use two block types to assess the independent contribution of regular locations and regular actions: That is, in action blocks we will present regular targets at random locations but with a consistent color, probing a consistent response-action. In location blocks the regular target will be presented at one location, but with unpredictable colors probing an unpredictable response. Possible outcomes of this follow-up experiment are: (1) Participants still do not learn the temporal regularity in any condition: Correspondence between action and location is not a prerequisite for implicit learning of temporal regularities, or the motor action must be more elaborate (e.g., mouse cursor movements). (2) Participants learn the temporal regularity in the location=action condition, but not in the location or action condition: Correspondence between action and location is a prerequisite for implicit learning of temporal regularities. (3) Participants learn the temporal regularity in the location=action and action condition, but not in the location condition: Only the action regularity is a prerequisite for implicit learning of temporal regularities, and the null findings in the previous experiment may have been caused by Simon interference. (4) Participants learn the temporal regularity in the location=action and location condition, but not in the action condition: Only the location regularity is a prerequisite for implicit learning of temporal regularities, null findings in the previous experiment may have been caused by Simon effects. (5) Participants learn the temporal regularity in all conditions: Both location regularities and action regularities can induce learning, but in the previous experiment such effects were probably disrupted by Simon interference. (6) Participants learn the temporal regularity in all conditions, but with varying strength: Both action and location are a prerequisite for implicit learning of temporal regularities, and they have a superadditive effect when occurring together.

In a psychophysical experiment based on the arcade game Whac-A-Mole (WAM), in which targets (moles) had to be hit using a computer cursor, Salet et al. (2021) showed that temporal regularities built into the WAM experiment (here: one of three targets appeared every 3 s) can be learned implicitly and improve performance expressed by reaction time (RT) and hit rate. That is, although their participants were completely unaware of the timing aspect of the experiment, they unintentionally utilized temporal information to guide behavior. In this study, the aim is to assess the action-perception coupling of implicit temporal learning. That is, whether the implicit temporal adaptation observed in Salet et al. (2021) results from learning where the regular stimulus is presented at regular onsets (perception); or learning what motor action to perform at regular onsets. Salet et al. (2021)'s study does not allow to distinguish between these two possibilities as the regularity’s spatial location was directly coupled to a unique motor action: Their participants could have learned to do three things at regular onsets: (1) where to spatially orient their attention; (2) what motor action to prepare in anticipation of regular’s onsets; or (3) both. With an extension of the WAM-design of Salet et al. (2021) we aim to distinguish between these three possible learning possibilities. To do so, we manipulate whether the regular feature is linked to a unique location or a unique motor action. We modify the WAM-design such that targets vary in location (left, top, right) and color (orange, green, purple). Participants place their index, middle, and ring finger on three buttons, each button corresponding to one of the three colors. In one half of the experiment, the temporal regularity concerns the feature 'location' (regular location condition; as in Salet et al., 2021). For example, every 3 s a target appears on the left, with an unpredictable color. This means that the motor action (button press with one of the three fingers) is not associated with this regularity. In the other half of the experiment, the temporal regularity concerns the feature 'color' thereby linking motor action with the regularity (regular action condition): For example, every 3 s a green target occurs, while the location of this target was randomized. Because the correct response (i.e. specific finger press) is defined by this color, a repetitive and meaningful motor action occurs only if the regular feature is 'color': Every three seconds a green target prompts a response with the same finger. Possible outcomes of this experiment, based on the three possible learning outcomes outlined above, are: (1) Implicit learning occurs in the regular location and action condition: Participants can both implicitly learn at regular onsets where to spatially orient their attention and what motor action to perform. (2) Implicit learning occurs in the regular location but not in the action condition: Participants only learn where to spatially orient their attention at regular onsets, but not what motor action to perform. (3) Implicit learning occurs in the regular action but not location condition: Participants only learn what motor action to perform at regular onsets, but not where to spatially orient their attention. (4) Implicit learning occurs neither in the regular location nor in the action condition: Participants do not pick up on any temporal regularity in this paradigm, which might suggest that a correspondence between action and location are a prerequisite for learning temporal regularities. Salet JM, Kruijne W, Van Rijn H (2021). Implicit learning of temporal behavior in complex dynamic environments. Psychonomic Bulletin and Review, 28:1270–1280. https://doi.org/10.3758/s13423-020-01873-x

Self-paced learning (SPL) mimics the cognitive mechanism of humans and animals that gradually learns from easy to hard samples. One key issue in SPL is to obtain better weighting strategy that is determined by minimizer function. Existing methods usually pursue this by artificially designing the explicit form of SPL regularizer. In this paper, we focus on the minimizer function, and study a group of new regularizer, named self-paced implicit regularizer that is deduced from robust loss function. Based on the convex conjugacy theory, the minimizer function for self-paced implicit regularizer can be directly learned from the latent loss function, while the analytic form of the regularizer can be even known. A general framework (named SPL-IR) for SPL is developed accordingly. We demonstrate that the learning procedure of SPL-IR is associated with latent robust loss functions, thus can provide some theoretical inspirations for its working mechanism. We further analyze the relation between SPL-IR and half-quadratic optimization. Finally, we implement SPL-IR to both supervised and unsupervised tasks, and experimental results corroborate our ideas and demonstrate the correctness and effectiveness of implicit regularizers.

In this report we examine whether cardiac interoceptive signals can modulate the development of aversive Pavlovian conditioning. During a learning phase, participants were presented with an aversive noise synchronized with their cardiac systole or diastole. This was followed by a modified Flanker task measuring attentional responses towards CS and a measure of subjective arousal and valence of CS. We aim to determine if cardiac signal can facilitate the development of contingency awareness, the development of attentional and subjective responses towards CS, and whether that can operate differentially in participants who are aware or unaware of contingencies.

This paper presents a literature review on self-regulated learning and then reports two investigations. The two investigations identified situations that seemed likely to afford opportunities for self-regulated learning to occur and followed what parents and teachers did to provide implicit support in these situations. The hypothesis was that the development in students of orientations to engage in self-regulatory effort and to value or even enjoy this experience occurs in part through certain relevant and recurring, elemental activities and interactions with significant others. The first investigation examined the implicit teachings involved in parent-child interactions around homework. It found that homework sessions were catalysts for parent-child dialogue around issues of autonomy and conformity. The second investigation coded high school students' essays for elements of self-regulated learning; most frequently used elements were emotion control, planning, and self-evaluation. The paper concludes that self-regulated learning comes about from the continuing interchange between students and the educating elements of their extended environments--adults and knowledgeable peers, various enacting curricula, and affording activities. (Contains approximately 70 references.) (JDD)

This article is from Frontiers in Psychology , volume 5 . Abstract We investigated the effect of a secondary task on implicit sequence learning in children and young adults. A serial reaction time (SRT) task was administered to 8-to-10 year old children and 18-to-22 year old adults. Participants reacted to the location of a target presented in one of four locations on the screen with a spatially corresponding response key. Unknown to participants, the location at which the target appeared was structured according to a deterministic sequence. Occasionally, the black target dot was replaced by a red target dog. To assess the effect of attentional load on implicit sequence learning, half of the participants of each age group was assigned to the single task condition, while the other half executed the task under dual task conditions. Whereas participants in the single task condition could ignore the change in target identity, dual task participants additionally had to count the number of times the black dot was replaced by a red dog to increase the attentional load. Sequence learning was tested under single task conditions in both conditions. Z-transformed results indicate that young adults generally showed more sequence learning than children. Importantly, the secondary task had no effect on sequence learning in children, since children learned as much under dual task conditions as under single task conditions. Adults, on the other hand, showed a different result pattern, as they displayed more sequence learning under single task than under dual task conditions. We surmise that this result is due to the vainly attempt of adults, but not children, to integrate both sequences.

In this project we will investigate how the expresion of Implicit Learning (IL) is modulated by Cognitive Control. We will use different approaches to investigate this issue: a) Looking at IL sequential effects (reduction in the expression of IL after a non-sequential trials; Jiménez, Vaquero & Lupiáñez, 2009), b) Transfering to a new context involving or not involving the activation of a control set, and c) Inhibiting control brain areas by means of TMS stimulation .

This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory and real-world settings. The model is used to understand the effect of user behavior on the performance of a learning algorithm for ranked retrieval. We explore a wide range of possible user behaviors and find that learning from implicit feedback can be surprisingly robust. This complements previous results that demonstrated our algorithm's effectiveness in a real-world search engine application.

This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory and real-world settings. The model is used to understand the effect of user behavior on the performance of a learning algorithm for ranked retrieval. We explore a wide range of possible user behaviors and find that learning from implicit feedback can be surprisingly robust. This complements previous results that demonstrated our algorithm's effectiveness in a real-world search engine application.

This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory and real-world settings. The model is used to understand the effect of user behavior on the performance of a learning algorithm for ranked retrieval. We explore a wide range of possible user behaviors and find that learning from implicit feedback can be surprisingly robust. This complements previous results that demonstrated our algorithm's effectiveness in a real-world search engine application.

This article is from PLoS ONE , volume 9 . Abstract Background: Motor learning is central to domains such as sports and rehabilitation; however, often terminologies are insufficiently uniform to allow effective sharing of experience or translation of knowledge. A study using a Delphi technique was conducted to ascertain level of agreement between experts from different motor learning domains (i.e., therapists, coaches, researchers) with respect to definitions and descriptions of a fundamental conceptual distinction within motor learning, namely implicit and explicit motor learning. Methods: A Delphi technique was embedded in multiple rounds of a survey designed to collect and aggregate informed opinions of 49 international respondents with expertise related to motor learning. The survey was administered via an online survey program and accompanied by feedback after each round. Consensus was considered to be reached if ≥70% of the experts agreed on a topic. Results: Consensus was reached with respect to definitions of implicit and explicit motor learning, and seven common primary intervention strategies were identified in the context of implicit and explicit motor learning. Consensus was not reached with respect to whether the strategies promote implicit or explicit forms of learning. Discussion: The definitions and descriptions agreed upon may aid translation and transfer of knowledge between domains in the field of motor learning. Empirical and clinical research is required to confirm the accuracy of the definitions and to explore the feasibility of the strategies that were identified in research, everyday practice and education.

This article is from PLoS ONE , volume 9 . Abstract Background: Motor learning is central to domains such as sports and rehabilitation; however, often terminologies are insufficiently uniform to allow effective sharing of experience or translation of knowledge. A study using a Delphi technique was conducted to ascertain level of agreement between experts from different motor learning domains (i.e., therapists, coaches, researchers) with respect to definitions and descriptions of a fundamental conceptual distinction within motor learning, namely implicit and explicit motor learning. Methods: A Delphi technique was embedded in multiple rounds of a survey designed to collect and aggregate informed opinions of 49 international respondents with expertise related to motor learning. The survey was administered via an online survey program and accompanied by feedback after each round. Consensus was considered to be reached if ≥70% of the experts agreed on a topic. Results: Consensus was reached with respect to definitions of implicit and explicit motor learning, and seven common primary intervention strategies were identified in the context of implicit and explicit motor learning. Consensus was not reached with respect to whether the strategies promote implicit or explicit forms of learning. Discussion: The definitions and descriptions agreed upon may aid translation and transfer of knowledge between domains in the field of motor learning. Empirical and clinical research is required to confirm the accuracy of the definitions and to explore the feasibility of the strategies that were identified in research, everyday practice and education.

Research has shown that teaching second language (L2) learning strategies explicitly promotes an increase in strategy use and in oral proficiency. Consequently, a checklist based on the six types of strategies from Oxford's taxonomy (1990) was created to analyze strategic instruction in the most common textbooks used in the last year of Higher Secondary Education in Spain. The study considered whether there was explicit strategy instruction and its location (within the units [Internal] or in other sections [External]) in course books, and what specific strategies were explicitly taught for the two oral skills, listening and speaking. Results showed, first, that there was explicit internal and external instruction of L2 learning strategies both for listening and speaking, but not in all the books; second, that there was significantly more implicit use than explicit instruction, and less explicit instruction in the units of the textbooks than in specific extra sections in the textbook or in support material; and finally, that internal explicit instruction of strategies remains very limited; and thus, L2 learning strategy instruction, competence and use may not be sufficiently encouraged in those textbooks.

Similarities and differences in implicit procedural learning and recording of ERP between subjects in developmental coordination disorder group and in control group using an adapted version of a serial reaction time task in motor imagery and action execution conditions

Intensive early behavioral interventions are the most effective treatment for Autism Spectrum Disorder (ASD), but almost half of the children do not make significant gains. Implicit learning skills are integral to behavioral interventions in ASD. Yet there is inconsistency in the literature as to whether individuals with ASD have difficulties with such learning. In this pilot award, we use multiple levels of inquiry to address implicit learning abilities in a heterogeneous sample of young children with ASD. Preliminary data from the learning task suggests that when data is averaged together from children with ASD and compared to typically developing (TD) children, it appears that children with ASD are not able to learn implicitly. However, while the sample is still small, we have observed individual differences in the expression of learning, with some but not all children with ASD learning on the task. Determining individual variability for learning in ASD is consistent with the primary goal of the project and it is the hope that this information can be used in the future to tailor behavioral interventions for children with ASD.

This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform a sequence, or chain, of queries with a similar information need. Using query chains, we generate new types of preference judgments from search engine logs, thus taking advantage of user intelligence in reformulating queries. To validate our method we perform a controlled user study comparing generated preference judgments to explicit relevance judgments. We also implemented a real-world search engine to test our approach, using a modified ranking SVM to learn an improved ranking function from preference data. Our results demonstrate significant improvements in the ranking given by the search engine. The learned rankings outperform both a static ranking function, as well as one trained without considering query chains.

Approved protocol for the manuscript submitted to Consciousness and Cognition (in princinple acceptance).

Approved protocol for the manuscript submitted to Consciousness and Cognition (in princinple acceptance).

The human cognitive system is stunningly powerful in some respects yet surprisingly limited in others. We can recognize an object or a face in a single glimpse and type 70 words per minute, yet we cannot hold more than a few objects at a time in visual working memory or split our attention to several locations. Attention and working memory impose major capacity limitations in cognitive processing. This ARO funded project examines the role of implicit learning in overcoming cognitive limitations. It hinges on the observation that humans process a visual display more quickly when it is encountered for a second time. The project addresses three fundamental properties about spatial learning. First, does learning have a capacity limit? Second, is learning reduced when attention is tied up by a secondary load? Third, how much does the learning ability vary across individuals, and what are the cognitive and brain mechanisms that separate good learners from poor learners? We found that spatial context learning is automatic, flexible, has high capacity, and applies to most individuals. This mechanism can potentially overcome cognitive limitations in human attention and working memory, and may assist soldiers in spatial navigation.

Virtual reality promotes prosocial behavior on various issues, including homelessness, ageism, and the environment. Recently researchers have explored the potential for a virtual reality experience to promote an empathic perspective transformation with promising results. The purpose of my proposed research is to investigate and explain the effectiveness of virtual reality as a strategy to bring about a transformative learning experience through historical empathy and reduce implicit racial bias. The expected outcomes of my research will show virtual reality as an intervention to reduce implicit racial bias through historical empathy. Consequently, indicating engagement in virtual reality is more effective than traditional methods, a 2D desktop or written transcript. Results of this proposed study are hypothesized to demonstrate that virtual reality is a beneficial strategy for prosocial behavior. [For the full proceedings, see ED631897.]

Generative adversarial networks (GANs) provide an algorithmic framework for constructing generative models with several appealing properties: they do not require a likelihood function to be specified, only a generating procedure; they provide samples that are sharp and compelling; and they allow us to harness our knowledge of building highly accurate neural network classifiers. Here, we develop our understanding of GANs with the aim of forming a rich view of this growing area of machine learning---to build connections to the diverse set of statistical thinking on this topic, of which much can be gained by a mutual exchange of ideas. We frame GANs within the wider landscape of algorithms for learning in implicit generative models--models that only specify a stochastic procedure with which to generate data--and relate these ideas to modelling problems in related fields, such as econometrics and approximate Bayesian computation. We develop likelihood-free inference methods and highlight hypothesis testing as a principle for learning in implicit generative models, using which we are able to derive the objective function used by GANs, and many other related objectives. The testing viewpoint directs our focus to the general problem of density ratio estimation. There are four approaches for density ratio estimation, one of which is a solution using classifiers to distinguish real from generated data. Other approaches such as divergence minimisation and moment matching have also been explored in the GAN literature, and we synthesise these views to form an understanding in terms of the relationships between them and the wider literature, highlighting avenues for future exploration and cross-pollination.

Implicit learning refers to that people acquire new knowledge (structures or rules) without conscious awareness. Previous studies have shown that when the contrast of group identities was highlighted, learning accuracy of the in-group facial feedback group was significantly higher than the out-group facial feedback group at the least difficulty level. But few studies investigate the Influence of different groups’ facial feedback types on implicit learning of different difficulty levels concretely. Here, we attempt to conduct two experiments to explore how different groups’ facial feedback type impact implicit rule learning on different difficulty levels. We will use angry faces as negative feedback and happy faces as positive feedback to improve ecological validity. In experiment 1, different groups’ facial feedback types(all in-group, all out-group) will be used as the between-subjects variable. In experiment 2, only the feedback types will be changed (in-group feedback in level 1&2 out-group feedback in level 3&4, out-group feedback in level 1&2 in-group feedback in level 3&4) to explore the influence mechanism of facial feedback on implicit learning.

In most problem-solving activities, feedback is received at the end of an action sequence. This creates a credit-assignment problem where the learner must associate the feedback with earlier actions, and the interdependencies of actions require the learner to either remember past choices of actions (internal state information) or rely on external cues in the environment (external state information) to select the right actions. We investigated the nature of explicit and implicit learning processes in the credit-assignment problem using a probabilistic sequential choice task with and without external state information. We found that when explicit memory encoding was dominant, subjects were faster to select the better option in their first choices than in the last choices; when implicit reinforcement learning was dominant subjects were faster to select the better option in their last choices than in their first choices. However, implicit reinforcement learning was only successful when distinct external state information was available. The results suggest the nature of learning in credit assignment: an explicit memory encoding process that keeps track of internal state information and a reinforcement-learning process that uses state information to propagate reinforcement backwards to previous choices. However, the implicit reinforcement learning process is effective only when the valences can be attributed to the appropriate states in the system either internally generated states in the cognitive system or externally presented stimuli in the environment.

The aim is to investigate whether patients with amnesic mild cognitive impairment acquire information in the same manner as cognitively unimpaired older adults, or whether they benefit more/less from certain learning conditions (e.g., instructions) because of their explicit memory deficit. Participants of both groups undergo testing in a new contingency learning task using ecologically valid stimuli (object-location associations). This assesses the impact of implicit or explicit instructions, or a combination of both, on later memory performance. Based on these assessments we determine task parameters that enhance behavioural indicators of learning and memory.

This work advances basic research in the areas of learning and training. One product is a conceptual framework, which addresses the ways explicit and implicit knowledge interact to produce skills. This framework suggests that human performance may be controlled by either a subconceptual knowledge base (the implicit mode) or application of a symbolic conceptual model (the explicit mode). A computational cognitive architecture, CLARION, significantly different from other existing cognitive architectures, is developed in this work to capture a range of data related to the interaction. It helps us to explain (and eventually to predict) training and learning processes. The results of the experiments support the theory of the interactions of implicit and explicit learning processes during skill acquisition. The outcomes (data, models, and theories) provide a more detailed, clearer and more comprehensive perspective on skill learning.

The process of implicit learning is a phenomenon that has been studied for decades, but its implications for, and practical applications to, applied game design have been almost completely unexplored. This is seen as a major gap in the game-based learning literature, as the field has historically struggled to facilitate transfer of knowledge and skill gained in the game to scenarios outside the game (such as standardised competence tests). It is suggested that a lot of learning in games is implicit and results in tacit knowledge - difficult to explicate - which is why we believe it is prudent to study the process of implicit learning as it happens in games and how it is impacted by game design choices. This will allow educators to improve overall learning outcomes and contribute to our understanding of the complex learning mechanism at work during interactive media gameplay. In this study we seek to introduce implicit learning to applied game design, by exploring it in the context of cognitive load theory and attentional effects. To do this we will use a variation of the sequence learning paradigm in the context of a web-based game.

This article is from PLoS ONE , volume 9 . Abstract In this study we aim to examine how the implicit learning of statistical regularities of successive stimuli affects the ability to exert cognitive control. In three experiments, sequences of flanker stimuli were segregated into pairs, with the second stimulus contingent on the first. Response times were reliably faster for the second stimulus if its congruence tended to match the congruence of the preceding stimulus, even though most participants were not explicitly aware of the statistical regularities (Experiment 1). In contrast, performance was not enhanced if the congruence of the second stimuli tended to mismatch the congruence of the first stimulus (Experiment 2). The lack of improvement appears to result from a failure of learning mismatch contingencies (Experiment 3). The results suggest that implicit learning of inter-stimulus relationships can facilitate cognitive control.

This article is from PLoS ONE , volume 9 . Abstract In this study we aim to examine how the implicit learning of statistical regularities of successive stimuli affects the ability to exert cognitive control. In three experiments, sequences of flanker stimuli were segregated into pairs, with the second stimulus contingent on the first. Response times were reliably faster for the second stimulus if its congruence tended to match the congruence of the preceding stimulus, even though most participants were not explicitly aware of the statistical regularities (Experiment 1). In contrast, performance was not enhanced if the congruence of the second stimuli tended to mismatch the congruence of the first stimulus (Experiment 2). The lack of improvement appears to result from a failure of learning mismatch contingencies (Experiment 3). The results suggest that implicit learning of inter-stimulus relationships can facilitate cognitive control.

Is statistical learning of a salient distractor’s color implicit, inflexible and distinct from inter-trial priming?

Is statistical learning of a salient distractor’s color implicit, inflexible and distinct from inter-trial priming?