Individual Learning Performance Research Articles

Exploring breed differences in discrimination, reversal learning, and resistance to extinction in the domestic dog (Canis familiaris)

Learning is crucial for shaping domestic dogs’ behaviour through life experiences, yet not all breeds exhibit the same learning aptitude towards a particular task. The current study’s objective was to identify differences in behaviour and learning performance across and within five breed clades and elucidate the underlying factors contributing into these variations. Dogs (n = 111) from five breed clades (UK Rural, Retrievers, Asian Spitz, European Mastiff, and New World) participated in a virtual learning task with their owners. Owners completed validated questionnaires of Impulsivity and Reward Responsiveness. The learning task comprised of reinforcing an arbitrary behaviour (hand-touch) through multiple sessions of Acquisition (reinforcing the hand-touch), Discrimination (reinforcing the hand-touch on one of two hands) and Reversal Learning (reinforcing the hand-touch on the opposite hand), followed by a single session of Extinction (hand-touch not reinforced). Results showed notable differences across the studied breed clades in certain learning and behavioural components. However, the observed disparities may not be entirely attributed to inherent cognitive differences among the breed clades but rather potentially influenced by contextual factors such as the human-dog communication dynamics associated with breeds’ cooperativity. Furthermore, breed clades differed in the contributing factors predicting individual learning performances, which could highlight the potential effect of breeds’ historical function.

Safety first! Psychological safety as a driver of learning in functionally diverse, self-assembled teams

Purpose This study aims to explore psychological safety as a potential moderating mechanism for the relation between functional diversity and individual perceptions of learning, and functional diversity and team performance in self-assembled teams. Design/methodology/approach To test these relationships, the authors conducted a cross-level, time-lagged, quasi-experiment, using a sample of 143 self-assembled teams. In one condition, participants formed into functionally diverse teams, and in another condition, participants formed functionally homogeneous teams. Findings Results suggest that functional diversity and psychological safety have an interactive effect on both individual learning and self-assembled team performance, albeit in different directions. Specifically, low psychological safety was more deleterious for individuals on functionally diverse teams than functionally homogeneous teams when it came to perceptions of learning, but the opposite was true when it came to team performance. Originality/value The results of this study indicate that it is critical to train team members on developing psychological safety, both in traditional and functionally diverse contexts.

Influences of Leaderboard Direction on Learning Performance and Satisfaction in Gamified E-Learning

The fast-growing use of gamification in e-learning underscores its potential to enhance individuals' learning performance and experience. However, the mechanisms through which key gamification element influences people's learning remain unclear. This study addresses this gap by investigating how distinct leaderboard directions influence individual learning performance and satisfaction. We conduct a randomized experiment to examine these effects and explore the underlying mechanisms. Our results show that upward leaderboard improves learning performance and satisfaction by fostering learning effort and active exploration. In contrast, downward leaderboard enhances learning performance and satisfaction through self-efficacy and self-expansion. Interestingly, the effect of lateral leaderboards on learning satisfaction appears not associated with the development of personal meaning. This study contributes to current research and practice by providing important insights for effective gamified e-learning design, implementation, and use.

Impact of interactive learning elements on personal learning performance in immersive virtual reality for construction safety training

To improve construction safety through proactive prevention strategies, it is essential to leverage virtual reality (VR) training programs that foster active learning through dynamic interaction between VR systems and learners. Addressing this need, this study proposed an interactive immersive VR (IVR)-based construction safety training framework, incorporating four interactive learning elements (ILEs): immediate feedback, basic interaction with objects, assembling objects, and knowledge testing. This study divided sixty trainees into two groups: one experienced the proposed novel interactive IVR-based training approach, while the other underwent traditional, non-interactive IVR-based training. To accurately evaluate the impact of the four ILEs on individual learning performance, this study conducted t-test analyses and utilized machine learning-based SHAP (Shapley Additive exPlanations) analysis to compare the results between both groups. The findings indicated that the proposed method significantly enhanced active learning, positively influencing the sensory and knowledge domains of trainees more effectively than the existing methods. Notably, 'ILE-(1). Immediate feedback' and 'ILE-(2). Basic interaction with objects' were identified as key factors in improving personal learning outcomes during training. This study contributes significantly to the field of management in engineering, demonstrating that interactive IVR-based training can offer a superior learning experience and enhance safety performance, thereby reducing accident rates and creating safer construction sites.

Content-Focused Formative Feedback Combining Achievement, Qualitative and Learning Analytics Data

Research that integrates Learning Analytics (LA) with formative feedback has been shown to enhance student individual learning processes and performance. Debates on LA-based feedback highlight the need to further understand what data sources are appropriate for LA, how soon the feedback should be sent to students and how different types of feedback promote learning. This study describes an empirical case of LA-based feedback in higher education and analyzes how content-focused feedback promotes student achievement. The model combines quantitative achievement indicators with qualitative data about student learning challenges to develop feedback. Data sources include student pretest results, participation in practice exercises as well as midterm and final exam grades. In addition, in-depth interviews with high-, medium- and low-performing students are conducted to understand learning challenges. Based on their performance, students receive content-focused feedback every two weeks. The results show statistically significant improvements in final grades, in addition to a higher rate of problem-solving participation among students who receive feedback compared to their peers who opt out of the study. The contributions to the area of LA-based formative feedback are the following: (a) a model that combines quantitative with qualitative data sources to predict and understand student achievement challenges, (b) templates to design pedagogical and research-based formative feedback, (c) quantitative and qualitative positive results of the experience, (d) a documented case describing the practical implementation process.

Predicting individual learning performance using machine‐learning hybridized with the teaching‐learning‐based optimization

AbstractReliable prediction of individual learning performance can facilitate timely support to students and improve the learning experience. In this study, two well‐known machine‐learning techniques, that is, support vector machine (SVM) and artificial neural network (ANN), are hybridized by teaching–learning‐based optimizer (TLBO) to reliably predict the student exam performance (fail‐pass classes and final exam scores). For the defined classification and regression problems, the TLBO algorithm carries out the feature selection process of both ANN and SVM techniques in which the optimal combination of the input variables is determined. Moreover, the ANN architecture is determined using the TLBO algorithm parallel to the feature selection process. Finally, four hybrid models containing anonymized information on both discrete and continuous variables were developed using a comprehensive data set for learning analytics. This study provides scientific utility by developing hybridized machine‐learning models and TLBO, which can improve the predictions of student exam performance. In practice, individual performance prediction can help to advise students about their academic progress and to take appropriate actions such as dropping units in subsequent teaching periods. It can also help scholarship providers to monitor student progress and provision of support.

Do Gender or Major Influence the Performance in Programming Learning? Teaching Mode Decision Based on Exercise Series Analysis.

Both traditional teaching and online teaching advocate individualized education. One of the difficulties on exploring possible improvements of instructional design is the challenging process of data collection. Existing research mainly focuses on the exam score of students but pays little attention to students' daily practice. As an effective method to handle time-series dataset, the generalized estimating equations (GEE) have not been used in this research field. Considering above issues, we first propose an experimental paradigm of programming performance analysis based on the performance record of students' daily practice-exam and finish collecting a complete time-series dataset in one semester, including students' individual attributes, learning behavior, and learning performance. Then, we propose an approach that analyzes practice-exam time-series dataset based on GEE to study the influence of individual attributes and learning behavior on learning performance. It is the first time to apply the GEE method for ordinal multinomial responses in this research field, by which we conclude several results that gender or major does have a certain difference on the programming learning. The longer the answer time and the less the cost time, the better the students' performance. Regardless of gender, students tend to cram for the exam and perform a little worse in the daily exercise. Finally, targeting at two important individual attributes, we give corresponding teaching mode decisions that university should teach students programming by major and teacher should give different teaching methods to students of different genders at different time points.

Primary school students’ foreign language anxiety in collaborative and individual digital game-based learning

Few studies have focused on the comparison between collaborative and individual digital game-based learning (DGBL) performance for students who study English as a Foreign Language (EFL). In collaborative DGBL, how the composition of foreign language anxiety (FLA) within groups of students affects students’ performance remains uncertain. This study aimed to examine the effects of anxiety composition on DGBL performance of primary school students with different FLA levels to inform collaborative DGBL instruction. Ninety-six fifth-graders from four classes were identified as low, moderate, and high anxiety students according to Foreign Language Classroom Anxiety Scale (FLCAS). Two classes were randomly assigned into collaborative DGBL while the other two classes in individual DGBL. The students in the collaborative DGBL were further grouped into 12 heterogeneous groups with anxiety composition of Low & Moderate (LM), Low & High (LH), Moderate & High (MH), and Low, Moderate & High (LMH). Those in the individual DGBL underwent individual gameplay learning. It was found that either collaborative or individual DGBL effectively assisted the students to reduce their FLA. The results also showed that the students in the heterogeneous groups generally had better DGBL performance than those who worked individually. Particularly, groups with anxiety composition of LM outperformed those with LH, those with MH, and those with LMH. The study suggests group composition be considered a critical factor that may enhance students’ learning with FLA in collaborative DGBL.

Effectiveness of Using Dormitory Rooms Based on The Capacity and Functional Performance of Users (Case Study: Male and Female Student Dormitory, Institut Teknologi Sumatra)

Dormitory facilities are essential accommodation facility that facilitated by universities that have a large number of students. The room’s level of effectiveness in a dormitory can be measured by the number of rooms, especially those that are private, such as bedrooms. Institut Teknologi Sumatera (ITERA), with many new students enrolled every year, must accommodate hundreds of students, especially those who come from outside the city. Due to the large number of students, the university management provided a solution to accommodate three people in one room. It gives various perceptions amongst the users about the effectiveness of space and its effect on user functional performance. This study aims to determine the level of effectiveness in using room space and its effect on individual learning performance. This study compares male and female dormitories based on the assessment aspect of several user perception variables. The method used in this research is based on the results of questionnaires distributed to students with aspects of assessment including privacy, territory, crowdedness, and adaptability. This study’s results are a parameter of space effectiveness based on space capacity and its effect on student learning performance. This finding is expected to become a reference for dormitory facilities to facilitate better.

Learners' interaction patterns in asynchronous online discussions: An integration of the social and cognitive interactions

AbstractStudying the networked nature of social and cognitive aspects of learner interactions is the key to understanding how successful collaborative learning occurs in asynchronous online discussion forums (AODFs). Guided by network science and multiplex network analysis, this study compared the differences of network structure and properties between the social (learners as nodes and commenting on the others' contributions as edges) and cognitive (learners as nodes and explicitly quoting the others' contributions as edges) networks within an AODF. It additionally examined the differences of individual measures between these two monolayer networks and their integrated two multiplex networks. The two multiplex networks were respectively framed in superimposed and unfold approaches. Moreover, correlation analysis was conducted to examine the relationships between individual measures and learning performance across the four networks. Results showed key differences at the network and individual levels between the social and cognitive networks. The two networks had different compositions of participants, and students in the cognitive network occupied more central positions in general. Besides, certain individual measures in the multiplex networks were relatively higher and more related to learning performance than those in the monolayer networks. These results indicate that integrating multi‐aspect information of collaboration may be more conducive to unveiling learners' interaction patterns in asynchronous online discussions. Practitioner notesWhat is already known about this topic? Studying the networked nature of the social and cognitive aspects of learner interactions is the key to understanding how successful collaborative learning occurs. Social network analysis and content analysis are two commonly used methods to analyse learner interactions in asynchronous online discussions. There is a lack of research examining learners' overall interaction patterns by integrating social and cognitive interactions. What this paper adds? This study framed cognitive interactions as a networked phenomenon to unveil the way learners participate in the cognitive aspect of learner interactions. Multiplex network analysis (MNA) was introduced to integrate social and cognitive interactions to understand learners' overall interaction patterns. Integrating social and cognitive interactions led to a more closer relationship between learner interactions and learning performance. Implications for practice and/or policy? The proposed approach for framing the cognitive network and the introduced approach of MNA could be jointly employed to discern learners' overall interaction pattern in asynchronous online discussions. Course facilitators and instructors should be aware of the inconsistencies in social and cognitive interactions and then simultaneously examine them so as to acquire an accurate understanding of learners' diverse interactions. Pedagogical strategies for simultaneously facilitating social and cognitive interactions could be used to better improve learning performance.

Effects of the group‐regulation promotion approach on students’ individual and collaborative learning performance, perceptions of regulation and regulation behaviours in project‐based tasks

AbstractGroup regulation has been recognised as an important factor affecting students' performances in project‐based learning. However, students often experience unsuccessful project outcomes due to several factors, such as unfocused negotiation and lack of project monitoring. In this study, a group regulation promotion approach was developed. The proposed approach consisted of a group‐regulated learning module that allows students to set learning goals, divide work and adjust their learning progress. There is also a platform for students to share their learning goals, observe others’ work and discuss with their peers. To evaluate the effectiveness of the proposed approach, a 6‐month experiment was conducted in a higher education context. A total of 50 undergraduate students aged 19–20 years old participated in this research. One class assigned as the experimental group learned with the proposed approach, whereas the other class assigned as the control group learned with the collaborative project‐based learning approach. The results revealed that the proposed approach benefited the students’ group learning performance, individual learning performance and their perception of group regulation. In addition, students who learned through the promotion mechanism showed more active learning behaviours. In sum, the integration of the group regulation promotion approach can be an effective means of enhancing students’ learning performance. Practitioner notesWhat is already known about this topic Collaborative project‐based learning has been regarded as a comprehensive approach for teaching and learning. Technologies benefit students by facilitating online and offline collaborative project‐based learning. Group regulation has been recognized as an important and challenging factor affecting students' performances in project‐based learning. What this paper adds A group regulation promotion approach was developed to encourage students to engage in continuous group regulation with their peers. A group‐regulated learning module was provided to help students set learning goals, divide work, and adjust their learning progress. A sharing platform was developed to assist student in sharing their learning goals, observing others' work, and discussing with their peers. The proposed approach promoted the students’ group learning performance, their individual learning performance, and active regulated learning behaviors. Implications for practice and/or policy The group regulation promotion approach is a potential strategy for implementing collaborative learning activities, especially for improving students’ active regulated learning behaviors. It is worth deeply investigating students’ regulated learning behaviors in collaborative learning activities.

Microglial activation in the right amygdala-entorhinal-hippocampal complex is associated with preserved spatial learning in AppNL-G-F mice

BackgroundIn Alzheimer`s disease (AD), regional heterogeneity of β-amyloid burden and microglial activation of individual patients is a well-known phenomenon. Recently, we described a high incidence of inter-individual regional heterogeneity in terms of asymmetry of plaque burden and microglial activation in β-amyloid mouse models of AD as assessed by positron-emission-tomography (PET). We now investigate the regional associations between amyloid plaque burden, microglial activation, and impaired spatial learning performance in transgenic mice in vivo. MethodsIn 30 AppNL-G-F mice (15 female, 15 male) we acquired cross-sectional 18 kDa translocator protein (TSPO-PET, 18F-GE-180) and β-amyloid-PET (18F-florbetaben) scans at ten months of age. Control data were obtained from age- and sex-matched C57BI/6 wild-type mice. We assessed spatial learning (i.e. Morris water maze) within two weeks of PET scanning and correlated the principal component of spatial learning performance scores with voxel-wise β-amyloid and TSPO tracer uptake maps in AppNL-G-F mice, controlled for age and sex. In order to assess the effects of hemispheric asymmetry, we also analyzed correlations of spatial learning performance with tracer uptake in bilateral regions of interest for frontal cortex, entorhinal/piriform cortex, amygdala, and hippocampus, using a regression model. We tested the correlation between regional asymmetry of PET biomarkers with individual spatial learning performance. ResultsVoxel-wise analyses in AppNL-G-F mice revealed that higher TSPO-PET signal in the amygdala, entorhinal and piriform cortices, the hippocampus and the hypothalamus correlated with spatial learning performance. Region-based analysis showed significant correlations between TSPO expression in the right entorhinal/piriform cortex and the right amygdala and spatial learning performance, whereas there were no such correlations in the left hemisphere. Right lateralized TSPO expression in the amygdala predicted better performance in the Morris water maze (β = -0.470, p = 0.013), irrespective of the global microglial activation and amyloid level. Region-based results for amyloid-PET showed no significant associations with spatial learning. ConclusionElevated microglial activation in the right amygdala-entorhinal-hippocampal complex of AppNL-G-F mice is associated with better spatial learning. Our findings support a protective role of microglia on cognitive function when they highly express TSPO in specific brain regions involved in spatial memory.

LTI-Connections Between Learning Management Systems and Gaming Platforms

E-learning standards like learning tools interoperability can support at realizing innovative learning scenarios in distributed architectures. A learning tools interoperability connection between a learning management system and a gaming platform offers possibilities like embedding a game into an online course and sending player-specific data back to the learning management system. This allows for a new and data-driven evaluation of students' individual learning performances, especially for alternative methods like qualifications-based learning. The learning tools interoperability-specified mechanisms can also be applied for implementing functionality to exchange students' competence profiles and traces within a knowledge-management eco-system portal that provides a toolkit for creating competence-based games that meet the requirements of qualifications-based learning as well as tools for creating game-specific analytics. As a first result, the authors made a prototypical implementation with a serious game prototype based on the unity game engine and unity analytics as analysis platform.

Spatiotemporal dissociation of fMRI activity in the caudate nucleus underlies human de novo motor skill learning

Motor skill learning involves a complex process of generating novel movement patterns guided by evaluative feedback, such as a reward. Previous literature has suggested anteroposteriorly separated circuits in the striatum to be implicated in early goal-directed and later automatic stages of motor skill learning, respectively. However, the involvement of these circuits has not been well elucidated in human de novo motor skill learning, which requires learning arbitrary action-outcome associations and value-based action selection. To investigate this issue, we conducted a human functional MRI (fMRI) experiment in which participants learned to control a computer cursor by manipulating their right fingers. We discovered a double dissociation of fMRI activity in the anterior and posterior caudate nucleus, which was associated with performance in the early and late learning stages. Moreover, cognitive and sensorimotor cortico-caudate interactions predicted individual learning performance. Our results suggest parallel cortico-caudate networks operating in different stages of human de novo motor skill learning.

General learning ability in perceptual learning

Developing expertise in any field usually requires acquisition of a wide range of skills. Most current studies on perceptual learning have focused on a single task and concluded that learning is quite specific to the trained task, and the ubiquitous individual differences reflect random fluctuations across subjects. Whether there exists a general learning ability that determines individual learning performance across multiple tasks remains largely unknown. In a large-scale perceptual learning study with a wide range of training tasks, we found that initial performance, task, and individual differences all contributed significantly to the learning rates across the tasks. Most importantly, we were able to extract both a task-specific but subject-invariant component of learning, that accounted for 38.6% of the variance, and a subject-specific but task-invariant perceptual learning ability, that accounted for 36.8% of the variance. The existence of a general perceptual learning ability across multiple tasks suggests that individual differences in perceptual learning are not "noise"; rather, they reflect the variability of learning ability across individuals. These results could have important implications for selecting potential trainees in occupations that require perceptual expertise and designing better training protocols to improve the efficiency of clinical rehabilitation.

Individual personality does not predict learning performance in a foraging context in female guppies, Poecilia reticulata

Considerable interindividual variation in behaviour, including learning ability and personality, exists within populations. Recent research has suggested that these two traits might covary; that is, the expression of certain personality traits might be correlated with learning ability. We experimentally tested this hypothesis under controlled laboratory conditions using female Trinidadian guppies. We tested for individual learning performance, measured as time to learn an association between a physical object and the presentation of food, both without (individual learning) and with (social learning) public information from conspecifics. Further, we quantified three ecologically relevant personality traits in individual fish in a fixed sequence: namely, exploration of a novel environment, sociability as the tendency to associate socially with conspecifics and boldness in the face of a simulated threat of predation. Each of these three personality traits was significantly repeatable, but they were not intercorrelated (i.e. did not form a behavioural syndrome). Individuals that needed fewer trials to feed from the objects initially had a higher probability of reaching the learning criterion and needed fewer trials to do so, but this learning performance was not related to repeatable personality traits across individuals. More exploratory individuals tended to learn faster during individual learning. When excluding individuals that had not learned, more social individuals were significantly faster at associative learning during social learning than less social individuals. Overall, we found no compelling evidence for any link between individual personality traits and learning performance, nor between the two modes of learning. Our results therefore suggest that individual personality does not predict learning performance and the observed independence of the two modes of learning tested suggests a lack of a domain-general learning capacity in female Trinidadian guppies, at least under our experimental conditions.

Students’ patterns of accessing time in a text structure learning system: relationship to individual characteristics and learning performance

This study developed a learning system that allows teachers to edit assignments designed to teach students the text structure strategy through the use of four phases: instructing, modeling, practicing, and reflecting. A 7-week instructional experiment was conducted in which 84 12th-grade students learned the text structure strategy using this system. The results produced several significant findings. First, the students demonstrated very different patterns of accessing time when using this system, making it possible to classify them into 3 categories or clusters of users: “low-practice-low-reflection students”, who spent little time using the system; “low-practice-high-reflection students” who spent most of their time in the reflecting phase, during which they constructed graphic organizers and wrote summaries primarily by referring to the teacher’s examples; and “high-practice-low-reflection students” who spent most of their time in the practicing phase, during which they constructed graphic organizers and wrote summaries without referring to the teacher’s examples. Second, the students’ patterns of accessing time were related to their prior knowledge, Web experience, and learning performance. In particular, the “low-practice-low-reflection students” had the lowest learning performance. The “low-practice-high-reflection students” had a higher frequency of using PCs to access the Web, a lower level of prior knowledge, and higher gain scores than the “high-practice-low-reflection students”. These findings are discussed, and several suggestions are proposed for future research work.

An in-depth analysis of the interaction transitions in a collaborative Augmented Reality-based mathematic game

ABSTRACTCollaborative learning has long been proved to be a crucial agent for enhancing students’ social skills, problem-solving abilities and individual learning performance. Understanding how students move from one phase to another in their collaboration process can inform educators of how best to facilitate such learning. However, this is still an area needing more vigorous research. This study explores the process of students’ co-construction of knowledge in a digital game-based learning environment using a sequential analysis approach, with the aim to identify the significant features of students’ interactional transitions that would potentially lead to better learning. To achieve this aim, we designed a collaborative learning environment in which 24 sixth graders worked in 6 groups to compete in an Augmented Reality-based mathematic game that we designed. The results from the analysis of their interaction show that phases of interaction in a digital game-based learning environment transited differently in many ways from those in online text-based forums, and that task types, modalities, participant characteristics and learning goals all played a crucial role in determining how learners co-constructed knowledge.

Effects of graded versus ungraded individual readiness assurance scores in team-based learning: a quasi-experimental study.

Pre-class preparation is a crucial component of team-based learning (TBL). Lack of preparation hinders both individual learning and team performance during TBL. The purpose of the present study was to explore how the grading of the individual readiness assurance test (iRAT) can affect pre-class preparation, iRAT performance and performance in the end-of-year examination. Using a quasi-experimental design, Year 1 and 2 students' download frequency for their pre-class materials, performance on iRAT and examination were examined under two conditions; (1) under which the iRAT was graded and (2) under which the iRAT was ungraded. Medical students (N = 220) from three cohorts were included in the study. Differences between both conditions were tested by means of six separate ANCOVAs, using medical school entry test scores as the covariate to account for potential cohort effects. Results revealed that students were downloading more pre-class materials prior to their TBL sessions, and were performed significantly better on iRAT when their performance was graded, even after controlling for cohort effects. Analysis of covariance demonstrated that performance on iRAT also appeared to affect performance on their examination scores. The results of the study suggest that grading has a positive effect on students' iRAT scores. Implications for TBL are discussed.

The significance of dealing with mistakes for student achievement and motivation: results of doubly latent multilevel analyses

From a constructivist perspective on learning, mistakes are seen as natural elements of learning processes. A supportive and constructive way of dealing with student mistakes has shown to affect students’ individual motivation and learning performances in a favorable way. In classroom settings, however, making mistakes is not just a personal but also a social event. Dealing with mistakes should therefore be considered as both student-level and classroom-level characteristic. This study investigates three aspects of dealing with mistakes and their relevance for students’ achievement and motivation in English as a foreign language by analyzing the aspects at student and classroom level. The aspects are (a) teacher attitude toward mistakes, (b) teacher response to student mistakes, and (c) students’ perception of mistakes as useful for learning. Analyzing data of 5266 students from 427 classes in German secondary schools, the results demonstrate that at student level, all three aspects of dealing with mistakes affect students’ individual achievement as well as motivation in English language class. At classroom level, none of the aspects affect student average achievement. Two aspects affect student average motivation at the classroom level, namely (a) teacher attitude toward mistakes and (c) students’ shared perception of the usefulness of mistakes for learning. Our results show that students’ individual and shared perception of dealing with mistakes affect students’ motivational and cognitive learning outcomes in different ways. Furthermore, our findings underline the relevance of teachers’ attitudes as well as students’ perceptions concerning mistakes for student learning and motivation in English as a foreign language class.