Analysis And Visualization of Online Learning Data Based on Crowd Sensing

2020 ◽  
Author(s):  
Zhongxian Bai
Keyword(s):  
Online Learning ◽  
Crowd Sensing ◽  
Learning Data

scholarly journals Engaging Student Teachers in An Online Teaching Pedagogies Module during COVID-19

2021 ◽  
Vol 10 (7) ◽  
pp. 62
Author(s):  
Peter Tiernan ◽  
Jane O'Kelly ◽  
Justin Rami
Keyword(s):  
Online Learning ◽  
Student Teachers ◽  
Online Teaching ◽  
Primary Teachers ◽  
Initial Teacher Education ◽  
Learning Tools ◽  
Teachers Perceptions ◽  
The Impact ◽  
Teaching Pedagogies ◽  
Learning Data

COVID 19 represented a major challenge for many educators, with teachers needing to pivot rapidly to using online learning tools in order to stay connected with their students. This was particularly relevant for teachers in the process of completing their Initial Teacher Education (ITE), whose programmes of study did not include online teaching components. The objective of this study was to develop and evaluate a module for teaching in online and blended learning environments for 244 post-primary teachers in ITE. This study begins by examining the impact of COVID-19 and the resulting pivot to online learning, this includes an overview of the challenges associated with online teaching. Next, the authors explain the module in detail, outlining the tools, strategies and activities provided for student teachers. This included peer-evaluated online micro-teaching components - which formed a major part of the learning. Data collection involved a questionnaire which gathered student teachers’ perceptions of the module and its approaches, the impact it had on their ability to teach during the COVID-19 pandemic, and the knowledge and skills useful for future practice. Findings suggested that the implementation of the developed module was successful in preparing student teachers to teach online, providing them with the tools and confidence necessary for success. Improvements suggested the development of differentiated pathways for student teachers who are more experienced with online teaching. 

Utilizing online learning data to design face-to-face activities in a flipped classroom: a case study of heterogeneous group formation

2020 ◽  
Vol 68 (5) ◽  
pp. 2055-2071
Author(s):  
Jeongyun Han ◽  
Sun Young Huh ◽  
Young Hoan Cho ◽  
SoHyun Park ◽  
Jinhan Choi ◽  
...  
Keyword(s):  
Online Learning ◽  
Flipped Classroom ◽  
Group Formation ◽  
Heterogeneous Group ◽  
Face To Face ◽  
Learning Data

scholarly journals THE STRESS PROFILE OF EARLY CHILDHOOD EDUCATION TEACHERS DURING ONLINE LEARNING

2021 ◽  
Vol 12 (2) ◽  
pp. 146-151
Author(s):  
Faqih Purnomosidi
Keyword(s):  
Early Childhood ◽  
Online Learning ◽  
Early Childhood Education ◽  
Memory Impairment ◽  
Stress Profile ◽  
Psychological Resources ◽  
Phenomenological Method ◽  
Childhood Education ◽  
Stress Symptoms ◽  
Learning Data

This study aims to determine the description of stress in Early Childhood Education (ECE) teachers during online learning. The approach in this study was qualitative with a phenomenological method. The number of informants in this study was seven informants. The informants were preschool teachers who make online learning. Data collection was obtained through interviews and observations. The results showed that the stress symptoms experienced by informants were in the form of memory impairment, decreased concentration, quickly excessive anxiety, loss of interest, inability to relax, and trouble sleeping. The source of stress for each informant was making online learning videos during the pandemic and the depletion of economic, social, and psychological resources.

scholarly journals Classroom Action Research on Thematic-Designed Online Learning for Contemporary Japanese Literature

IZUMI ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 316-327
Author(s):  
Hayun Nurdiniyah ◽  
Wafa' Hanim Askho ◽  
Ari Artadi
Keyword(s):  
Online Learning ◽  
Action Research ◽  
Learning Strategy ◽  
Japanese Literature ◽  
Student Understanding ◽  
Online Course ◽  
Literary Study ◽  
Research Model ◽  
Classroom Action Research ◽  
Learning Data

This study aims to implement contemporary Japanese literature learning with thematic designs as a learning strategy for 60 students in literary study classes (Poetry, Prose, and Drama) at Darma Persada University that were conducted online during the pandemic. This study was conducted using Kurt Lewin's Classroom Action Research model consisting of planning, acting, observing, and reflecting; particularly for the observing section, the assessment was measured using two indicators based on students’ understanding of the material and satisfaction with online learning. Data was collected using questionnaires and filled out via google form. The findings of this study indicate the level of student understanding of the material, the constraints of online learning, and feedback from experts. The findings are useful for improving Japanese literature learning, to be more precisely during the online course

scholarly journals Intensitas penggunaan gawai dan kontrol orang tua di RT 02/RW 04 Desa Tambahagung

2021 ◽  
Vol 10 (3) ◽  
pp. 680
Author(s):  
Windi Widyayati ◽  
Deka Setiawan ◽  
Siti Masfuah
Keyword(s):  
Online Learning ◽  
Social Interactions ◽  
Significant Problem ◽  
Phenomenological Method ◽  
Self Disclosure ◽  
The Social ◽  
Qualitative Phenomenological ◽  
Learning Data

This study aimed to analyze the social interactions in using gadgets of 10-year-old children in Desa Tambahagung viewed from the control and the intensity of using gadget. The benefit of this study was analyzing the form of changes in social interactions that occurred in children aged 10 years who used gadgets. This study described 10 years old children affected by the gadget. This study used a qualitative phenomenological method, which was conducted in Desa Tambahagung RT 04/RW 02. The objects of this research were ten 10-year-old children in the area who were already familiar with gadgets, especially during the Covid 19 pandemic, in which they were closer and often used gadgets as a means of communication and learning because schools had switched to online learning. Data were collected through observation, interviews, documentation, and recording. The results showed that using gadgets on the interaction of children aged 10 years did not show a significant problem because on average children were extrovert or open to others. They generally played gadgets together with their friends so that the communication and interaction was still good. The phenomenon that emerged in this study was that the device had an effect on children's emotions, nomophobia, children's self-disclosure with parents, and children's language.  

scholarly journals Research on Adaptive Learning Prediction Based on XAPI

2020 ◽  
Vol 10 (9) ◽  
pp. 679-684
Author(s):  
Jun Xiao ◽  
◽  
Lamei Wang ◽  
Jisheng Zhao ◽  
Aizhen Fu
Keyword(s):  
Online Learning ◽  
Adaptive Learning ◽  
Prediction Models ◽  
Machine Learning Algorithms ◽  
Data Sets ◽  
Online Learners ◽  
Learning Platform ◽  
Teaching Support ◽  
The Relationship ◽  
Learning Data

In the field of online learning, there is a problem of high student turnover rate. How to accurately identify learners and provide targeted teaching support services is an urgent problem for education researchers. In this paper, 1306 online learners majoring in finance from Shanghai Open University were selected as the subjects, and two kinds of data sets are adopted, which are learning data of online learning platform and learning behavior data of students based on xAPI, to analyze the relationship between learners' various online learning behaviors and learning achievements, and to determine the characteristics related to learning state of learners, describe the personalized learning state portrait, and select a variety of machine learning algorithms to build prediction model based on two data sets, to explore which data is more effective for building prediction models to identify potential risk learners. It is found that data mining analysis based on xAPI data has higher prediction accuracy than traditional online learning data.

Assessing Practical Accessibility in Online Courses Based on Local Conditions

2019 ◽  
pp. 392-423
Keyword(s):  
Online Learning ◽  
Online Courses ◽  
Learning Objects ◽  
Learning Object ◽  
Use Case ◽  
Digital Learning ◽  
Local Conditions ◽  
Midwestern University ◽  
Accessibility Issues ◽  
Learning Data

Another approach to exploring online learning data is to see what is not there or what is absent. One use case for this is “practical accessibility” or the accessibility accommodations in online learning courses (or learning objects). This chapter includes a review of the current extant literature, a close-in analysis of several dozen real-world courses (in static format) through an instructional design/developer lens, in service of the following objectives: 1) the drafting of an initial instrument that may be used to assess the accessibility level of an online learning course or digital learning object, 2) the identification of the most common accessibility issues in online courses at a Midwestern university (based on a sample setoff online courses), and 3) the identification of a model course with full or near-full accessibility and seeing what may be learned from that and from specific accessibility accommodations that may be beneficial in other contexts.

Creating and Analyzing Induced Decision Trees From Online Learning Data

2019 ◽  
pp. 118-134
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Online Learning ◽  
Decision Trees ◽  
Teaching And Learning ◽  
Research Question ◽  
Supervised Machine Learning ◽  
Data Visualizations ◽  
Learning Data

Decision trees may be created in various ways. They may be manually drawn based on data, or they may be induced directly from data using supervised machine learning. Decision trees induced from online learning data may evoke insights that may benefit teaching and learning. This work introduces a method for inducing decision trees and addresses how to set the parameters for the trees based on particular decision making and research question making. This work uses online learning data to create decision trees and to enable practical insights from the resulting data visualizations.

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