Suchergebnisse

This article reports the first meta-analysis of the L2 motivational self system (Dörnyei, 2005, 2009). A total of 32 research reports, involving 39 unique samples and 32,078 language learners, were meta-analyzed. The results showed that the three components of the L2 motivational self system (the ideal L2 self, the ought-to L2 self, and the L2 learning experience) were significant predictors of subjective intended effort (rs = .61, .38, and .41, respectively), though weaker predictors of objective measures of achievement (rs = .20, -.05, and .17). Substantial heterogeneity was also observed in most of these correlations. The results also suggest that the strong correlation between the L2 learning experience and intended effort reported in the literature is, due to substantial wording overlap, partly an artifact of lack of discriminant validity between these two scales. Implications of these results and directions for future research are discussed.

This paper investigates the attitudinal/motivational predictors of second language (L2) academic achievement. Young adult learners of English as a foreign language (N = 311) completed several self-report measures and the Single-Target Implicit Association Test. Examination of the motivational profiles of high and low achievers revealed that attachment to the L1 community and the ought-to L2 self were negatively associated with achievement, while explicit attitudes toward the L2 course and implicit attitudes toward L2 speakers were positively associated with it. The relationship between implicit attitudes and achievement could not be explained either by social desirability or by other cognitive confounds, and remained significant after controlling for explicit self-report measures. Explicit–implicit congruence also revealed a similar pattern, in that congruent learners were more open to the L2 community and obtained higher achievement. The results also showed that neither the ideal L2 self nor intended effort had any association with actual L2 achievement, and that intended effort was particularly prone to social desirability biases. Implications of these findings are discussed.

This paper reports the first investigation in the second language acquisition field assessing learners' implicit attitudes using the Implicit Association Test, a computerized reaction-time measure. Examination of the explicit and implicit attitudes of Arab learners of English (N = 365) showed that, particularly for males, implicit attitudes toward L2 speakers are associated with self-reported openness to the L2 group and with strength of correlations among attitudinal and motivational variables. Implicit attitudes also moderated important paths in the L2 Motivational Self System. The paper concludes that implicit attitudes seem to be a meaningful individual difference variable, adding a new dimension to our understanding of language motivation.

Directed motivational currents, unique and intense goal-directed motivational surges lasting over a period of time, have received increasing attention recently. This article reports the first systematic review of this phenomenon. A total of 21 reports appearing between 2013 and 2020 were included in the analysis. The results show that the majority of empirical reports were small-scale qualitative studies (median = 18 participants). The evidence on the three characteristics proposed as necessary and/or distinguishing conditions of directed motivational currents (vision, salient facilitative structure, and positive affect) is inconclusive due to the presence of directed motivational currents cases not exhibiting these features, and the absence of direct comparative analyses with non-directed motivational currents cases. A few intervention studies (N = 4) were conducted, but their results are also inconclusive due to a number of methodological limitations. Contrary to the claim that directed motivational current experiences are the "optimal form" of motivation, the results additionally showed that these experiences could lead to intense stress, anxiety, depression, sleeplessness, and panic attacks, thereby raising ethical concerns about deliberately inducing directed motivational currents in learners. We conclude that, although the concept of directed motivational currents is promising, more research is needed to reach a better understanding of its potential. We end this article by suggesting directions for future research into directed motivational currents, including renaming them as sustained flow.

AbstractAlthough an important goal of learner peer feedback is promoting critical thinking, little attention has been paid to the nature of the topic, particularly whether it is controversial. In this article, we report on a study where 52 English majors were asked to comment on essays written by their peers using the PeerMark module of Turnitin. Half of the essays were about controversial topics in the Saudi society (e.g., women driving and banning cigarettes), whereas the other half were less controversial (e.g., importance of sleep and respecting parents). Our results showed that the participants provided significantly more critical, global comments on controversial essays. At the same time, this increase in global comments did not come at the expense of local, language-related comments—in that the participants did not provide significantly fewer language comments on controversial essays. The participants also reported favorable attitudes toward this task due to the convenience and anonymity of online feedback, thus allowing them to express their opinions more freely on controversial topics. We therefore concluded that utilizing an online platform that permits double-blind peer review on controversial essays seems to have to the potential to stimulate critical thinking among language learners.

AbstractContract cheating, the act of students enlisting others to complete academic assignments on their behalf, poses a significant challenge in academic settings, undermining the integrity of education and assessment. It involves submitting work that is falsely represented as the student's own, thus violating academic standards and ethics. The advent of artificial intelligence-based language models, such as ChatGPT, has raised concerns about the potential impact of contract cheating. As these language models can generate human-like text with ease, there are concerns about their role in facilitating and increasing contract cheating incidents. Innovative approaches are thus needed to detect contract cheating and address its implications for academic integrity. This study introduces a machine learning (ML) model focused on identifying deviations from a learner's unique writing style (or their linguistic fingerprint) to detect contract cheating, complementing traditional plagiarism detection methods. The study involved 150 learners majoring in engineering and business who were studying English as a foreign language at a college in Saudi Arabia. The participants were asked to produce descriptive essays in English within a consistent genre over one semester. The proposed approach involved data preprocessing, followed by transformation using Term Frequency-Inverse Document Frequency (TF-IDF). To address data imbalance, random oversampling was applied, and logistic regression (LR) was trained with optimal hyperparameters obtained through grid search. Performance evaluation was conducted using various metrics. The results showed that the ML model was effective in identifying non-consistent essays with improved accuracy after implementing random oversampling. The LR model achieved an accuracy of 98.03%, precision of 98.52%, recall of 98.03%, and F1-score of 98.24%. The proposed ML model shows promise as an indicator of contract cheating incidents, providing an additional tool for educators and institutions to uphold academic integrity. However, it is essential to interpret the model results cautiously, as they do not constitute unequivocal evidence of cheating but rather serve as grounds for further investigation. We also emphasize the ethical implications of such approaches and suggest avenues for future research to explore the model's applicability among first-language writers and to conduct longitudinal studies on second-language learners' language development over longer periods.

Abstract

Background: Happiness at work is an important factor in employee satisfaction, productivity and retention. This study aimed to investigate the relationship between perceived manager's emotional intelligence and happiness at work, and whether job satisfaction and affective organizational commitment mediate this relationship.

Method: A questionnaire was distributed online to a random sample of 350 schoolteachers in Saudi public schools teaching different majors.

Results: Structural equation modelling results showed that satisfaction and affective organizational commitment fully mediated the relationship between perceived manager's emotional intelligence and happiness at work.

Conclusion: Our results support the hypothesis that perceived manager's emotional intelligence influences employee happiness through its influence on increasing or decreasing job satisfaction and affective organizational commitment. These findings therefore provide insight into employee's wellbeing and potentially how to promote it.