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Blended Learning (BL) creates a 'rich' educational environment with multiple technologyenabled communication forms in both face-to-face and online teaching. Students' characteristics are closely related to the learning effectiveness in the BL environment. Students' ability to direct themselves in learning and to utilise learning technologies can affect student learning effectiveness. This study examined the impacts of self-directed learning, technology readiness, and learning motivation on the three presences (social, teaching, cognitive) among students undertaking subjects in BL and non-BL (NBL) settings. The results indicated that the BL environment provides good facilitation for students' social involvement in the class. Student technology readiness plays a stronger role in impacting the teaching presence in a BL environment than NBL environment. These findings imply that a proper BL setting creates a cohesive community and enhances collaborations between students. Prior training of learning technologies can potentially enhance students' teaching presence.

Purpose This era is an era of social media (SM); thus, it is an essential tool for communication among individuals and organizations. The excessive use of SM by employees has raised many questions about their job performance. Therefore, there is a dire need to investigate the effects of SM use on an employee’s job performance mediated by knowledge exchange. Furthermore, the purpose of this paper is to examine how the organization’s SM rules can moderate the relationship between personal and work-related use of SM with information sharing and obtaining information. Design/methodology/approach Quantitative methodology was used and randomly 1,200 questionnaires data were collected physically from the employees of the public and private sectors in Pakistan. To examine the hypothesized relationships, partial least squares (PLS), rather than covariance-based structural equation modeling, was used to analyze the data. For this reason, multivariate technique, Smart PLS-3.2.1, was used for data analysis. Findings The findings of this study demonstrated that personal and work-related use of SM could enhance employees’ job performance through knowledge exchange, and SM rules have adverse impacts on the relationships between SM use and knowledge exchange. Originality/value This study provides a novel model for the investigation of whether SM use affects employees’ job performance. Furthermore, it will help the policy makers and researchers regarding the management of SM use at work.

Despite the popularity of massive open online courses (MOOCs), only a small portion of the course participants successfully complete the course. The low completion rate can be partially attributed to the mismatch between the participants' expectations and value delivered by the courses. Therefore, this study leverages MOOC reviews to investigate the focal point and sentiment of the learners by combining machine learning techniques and statistical analysis. Several text mining methods (ie, simplified Chinese‐linguistic inquiry and word count dictionary, word embeddings, and bidirectional long short‐term memory model) are combined to automatically extract the emotional and cognitive aspects, review focal point, and sentiment from the learner discourse. Multiple linear regression (MLR) analysis is performed to examine the relationships between the learner sentiment and the extracted content features. Using a set of real data from NetEase online open courses, our results reveal that the MOOC reviews mostly pertain to teaching and platform rather than the course content. Furthermore, the social process and personal concerns appear more frequently in the learner discourse. Overall, the learners exhibit positive attitudes towards teaching and platform and negative attitudes towards issues related to the course content. This study contributes to the literature regarding the MOOC research methodologies and provides a deeper understanding of the learner discourse behaviour in MOOCs.

Words representing objects (nouns) and words representing actions (verbs) are essential components of speech across languages. While there is evidence regarding the organizational principles governing neural representation of nouns and verbs in monolingual speakers, little is known about how this knowledge is represented in the bilingual brain. To address this gap, we recorded neuromagnetic signals while highly proficient Spanish–Basque bilinguals performed a picture-naming task and tracked the brain oscillatory dynamics underlying this process. We found theta (4–8 Hz) power increases and alpha–beta (8–25 Hz) power decreases irrespectively of the category and language at use in a time window classically associated to the controlled retrieval of lexico-semantic information. When comparing nouns and verbs within each language, we found theta power increases for verbs as compared to nouns in bilateral visual cortices and cognitive control areas including the left SMA and right middle temporal gyrus. In addition, stronger alpha–beta power decreases were observed for nouns as compared to verbs in visual cortices and semantic-related regions such as the left anterior temporal lobe and right premotor cortex. No differences were observed between categories across languages. Overall, our results suggest that noun and verb processing recruit partially different networks during speech production but that these category-based representations are similarly processed in the bilingual brain.

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Picture naming tasks are currently the gold standard for identifying and preserving language-related areas during awake brain surgery. With multilingual populations increasing worldwide, patients frequently need to be tested in more than one language. There is still no reliable testing instrument, as the available batteries have been developed for specific languages. Heterogeneity in the selection criteria for stimuli leads to differences, for example, in the size, color, image quality, and even names associated with pictures, making direct cross-linguistic comparisons difficult. Here we present MULTIMAP, a new multilingual picture naming test for mapping eloquent areas during awake brain surgery. Recognizing that the distinction between nouns and verbs is necessary for detailed and precise language mapping, MULTIMAP consists of a database of 218 standardized color pictures representing both objects and actions. These images have been tested for name agreement with speakers of Spanish, Basque, Catalan, Italian, French, English, German, Mandarin Chinese, and Arabic, and have been controlled for relevant linguistic features in cross-language combinations. The MULTIMAP test for objects and verbs represents an alternative to the Oral Denomination 80 (DO 80) monolingual pictorial set currently used in language mapping, providing an open-source, standardized set of up-to-date pictures, where relevant linguistic variables across several languages have been taken into account in picture creation and selection.

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