The Information Communication Technology Implementation in English Teaching During The Covid-19 Pandemic

Online learning has become a requirement during the COVID-19 pandemic. The Ministry of Education asks the teachers and students to use online classes during the pandemic. Teaching English using ICT is a challenging condition for teachers. Not all teachers are familiar with ICT. This paper aims to describe the ICT Role and implementation in Teaching English during the COVID-19 pandemic. Method: this is a literature review. Literature was searched in Science Direct and Google Scholar databases. Keywords were COVID-19, English Teaching, ICT, implementation, role. Results revealed that ICT in English Teaching is started from CALL (Computer Assisted Language Learning), TELL (Technology-Enhanced Language Learners), LMS (Learning Management System), and blended learning. YouTube and WhatsApp are preferred to be done because it is practical. Performance-based assessment is important during teaching English subject because students can learn how to perform, speaking, and debating during the performance. In conclusion, there are many systems available for teaching English using ICT. The systems are CALL, TELL, LMS, blended, WhatsApp, YouTube, and Performance-Based Assessment. The main goal is students’ understanding of the English subjects. The choice depends on study goal, teachers’ and students’ preference also feasibilities.

Taking stock of the past: A psychometric evaluation of the Autobiographical Interview

Autobiographical memory (AM) involves a rich phenomenological re-experiencing of a spatio-temporal event from the past, which is challenging to objectively quantify. The Autobiographical Interview (AI; Levine et al., 2002, Psychology & Aging) is a manualized performance-based assessment designed to quantify episodic (internal) and semantic (external) features of recalled and verbally conveyed prior experiences. The AI has been widely adopted yet has not undergone a comprehensive psychometric validation. We investigated the reliability, validity, association to individual differences measures, and factor structure in healthy younger and older adults (N=352). Evidence for the AI's reliability was strong: the subjective scoring protocol showed high inter-rater reliability and previously identified age effects were replicated. Internal consistency across timepoints was robust, suggesting stability in recollection. Central to our validation, internal AI scores were positively correlated with standard, performance-based measures of episodic memory, demonstrating convergent validity. The two-factor structure for the AI was not well-supported by confirmatory factor analysis. Adjusting internal and external detail scores for the number of words spoken (detail density) improved trait estimation of AM performance. Overall, the AI demonstrated sound psychometric properties for inquiry into the qualities of autobiographical remembering.

Transfer from Spatial Education to Verbal Reasoning and Prediction of Transfer from Classroom-Based Neural Change

Assessing whether learning in one domain is transferable to abilities in other domains often eludes traditional testing. Thus, a question with bearing on the promise of neuroscience for education is whether neural changes that accompany in-school curriculum learning can improve prediction of learning transfer. Separately, debate in philosophy and psychology has long concerned whether spatial processes underlie seemingly nonspatial/verbal human reasoning (e.g., mental model theory; MMT). If so, education that fosters spatial cognition might yield transfer to improved verbal reasoning. Here, in real-world classrooms studied in a quasi-experimental design, a STEM curriculum devised to foster spatial cognition yielded improved spatial abilities and-consistent with MMT-transferred beyond the spatial domain to improved verbal reasoning. Further supporting MMT, the more students’ spatial ability improved, the more their verbal reasoning improved, and spatial ability improvement mediated curriculum transfer. At the neural level, longitudinal fMRI detected curriculum-driven changes in activity, connectivity, and representational similarity of brain regions implicated in spatial cognition. Critically, changes in spatial cognition-linked neural activity robustly predicted curriculum transfer-more accurately than testing and grades-and mediated this transfer. Reports by the National Research Council and others note that spatial abilities reliably predict STEM achievement, but that broad adoption of spatial cognition-focused curricula depends on classroom-based evidence of efficacy and mechanisms-of-change. The present findings support the real-world application of MMT to classrooms via “spatial education.” Further, demonstrating that in-school neural change can predict transfer over-and-above performance-based assessment suggests the long-term achievability of neurally-informed curriculum development that leverages neural change to identify and design transferable curricula.