Impact of Technology on Traditional Teaching - Learning Measures in The Era of Covid-19 Pandemic

The period of 21stcentury is frequently respected as the period of Innovations and Technology. Today, Technology plays a significant part in our life. It is conceivable as it were through technology that distances are no more hindrances and training can be brought to the understudy's doorstep. The effect of innovation can be felt in each conceivable field and one such field is education. Instruction in its overall sense is a structure of learning in which the information, abilities and propensities from a gathering of individuals are changed from one age to next through instructing, preparing and research. Today, like never before, the job of instructive innovation in educating is of incredible significance in light of the utilization of data and correspondence advancements (ICT). Instructive innovation is a coordinated cycle of applying present day innovation to improve the nature of education. It is an efficient method of conceptualizing the execution and assessment of the instructive cycle, for example learning and educating furthermore, help with the use of current instructive educating methods. This paper features the significance of IT in educational areas, the effect of IT on study hall education, points of interest, and the detriments of IT.

When school comes home: How low-income families are adapting to distance learning

School campus closures due to COVID-19 forced transition to remote learning in March 2020, which continues in Fall 2020. Remote learning measures presents multiple challenges for low-income, minority families, and these families have been disproportionately affected by the COVID-19 crisis. We sought to understand the challenges they faced, including the lack of Internet access and devices, digital skills and lack of appropriate learning space at home.

Is Gamification a Magic Tool?: Illusion, Remedy, and Future Opportunities in Enhancing Learning Outcomes during and beyond the COVID-19

Gamification in education has been discussed with potential for further implementation at universities; however, practical suggestions concerning which key issues educators need to consider has far not been shared in academia. This study applied a qualitative approach using interview data with 24 students who participated in the business class with games as learning measures. It has found that most of them believed that gamification could be useful in reinforcing key themes and topics after having learnt them through traditional means: They appreciated the games as a supportive measure to ‘glue’ key knowledge to their learning. A significant drawback that they emphasised was that taking notes is not easy while they are involved in games, which made them unconfident and uncertain about the learning outcome. As a result, a conceptual framework for pedagogy stakeholders was proposed for further discussion of how to design a gamification-based curriculum effectively.

S82. REINFORCEMENT LEARNING IMPAIRMENT IN PATIENTS WITH EARLY-STAGE PSYCHOTIC BIPOLAR DISORDER

Background Abnormal reward sensitivity is a biosignature to mood disorders spectrum. Recent data suggested either elevated or preserved positive but impaired negative reinforcement learning in patients with bipolar disorder. Functional MRI studies provided extra evidence on heightened reward sensitivity in manic patients. Of note, these investigations mostly rest on chronically ill samples, conditions of whom may have been confounded by prolonged exposure to medications. This study aims to examine reinforcement learning performance and its relationship with symptomology in patients with early-stage psychotic bipolar disorder (BDP). Methods This study is based on 38 patients with early-stage BDP (defined by having received psychiatric treatment for first-episode BDP within 3 years since service entry) who have been euthymic for at least eight weeks and 40 demographically-matched controls. Reinforcement learning performance was evaluated using Gain-vs-Loss-Avoidance Task (GLAT), which measured the correct responses in both gain and loss-avoidance pairs with reinforcement probability at either 90% or 80% across four blocks in the training phase and one block in the test/transfer phase. Comparison analyses on reinforcement learning performance were conducted on two groups. Associations of reinforcement learning measures with symptom scores, cognitive functions and functioning measures were also tested. Results There was no group difference in gender, age or education level. Repeated-measures analysis of variance (ANOVA) showed significant main effects of group (F=6.52, p=0.013), block (F=43.71, p<0.001), probability (F= 5.58, p<0.001), and block x group (F=2.87, p=0.040) interaction. Post-hoc tests revealed that controls performed better than patients across blocks (p<0.05). Patients also showed a lower lose-shift rate (t= 2.21, p=0.03) and punishment-driven learning accuracy rates (t=2.42, p=0.018) than controls. Marginally significant main effect of stimulus pair (F=3.98, p=0.05) was revealed in the test phase, with controls showing a significantly higher preference in Frequent Winner vs Frequent Loser (FWFL) pair than patients (t=-2.25, p=0.028). No significant correlations between learning measures and any of the symptom dimensions in patient sample. Discussion Our preliminary findings provided a brief evidence on the negative reinforcement learning impairment in early-stage BDP patients. Further investigation is required to verify and confirm our results of impaired negative reinforcement learning in the initial course of bipolar disorder.