During the Covid-19 Pandemic, Students' Opinions on Distance Education in Department of Engineering

Karahoca, Dilek; Zaripova, Zulfiya F.; Bayanova, Almira R.; Чикилева, Л. С.; Avdeeva, E. L.; Xu, Baoyun

doi:10.3991/ijep.v12i2.29321

Cited by 9 publications

(7 citation statements)

References 16 publications

(17 reference statements)

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“…Some teachers prepared recorded videos and used Google Classroom, WebQuest but a majority of the teaching staff were not prepared for online education. It is also found that [31] students are happy with distance education model as that helps them to avoid academic disruption during the pandemic. Authors in [32] evaluated student's perception of using social media as an academic learning platform, collaboration, and engagement platform under confinement conditions and found its positive impact on academic performance.…”

Section: Globally Observed Covid-19 Challenges On Educationmentioning

confidence: 90%

Exploring Teaching and Learning Experience during COVID-19 Pandemic in Engineering Education

Arif

Shafiullah

2022

Sustainability

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The education system is continuously modernizing by accommodating the need due to the industrial revolution. Various teaching modes are also introduced including a diverse range of students, particularly in engineering education. The COVID-19 pandemic has disrupted normal education worldwide, forced to shut down campus activity for an extended period which forced Universities to adopt alternative approaches to continue student’s academic year. Engineering education faced significant challenges to find a realistic substitution for lab-based hands-on activity as well as group or team-based learning experiences. It is therefore very important to know the challenges and ways to address them. This paper evaluates the teaching and learning experiences observed in engineering education in Australia and abroad during the COVID-19 period compared to the pre-COVID period. The key motivation of this study is to identify key challenges arises due to COVID-19, develop Teaching & Learning (T & L) approaches to address these challenges and evaluate the effectiveness of the applied changes in the T & L approach, identify shortcomings, and find ways to improve them. The student feedback on selected engineering units have been collected from Deakin and Murdoch university in Australia to evaluate the performances of the applied changes. This data is considered as an authentic source of information to compare and identify the key challenges and effectiveness for students’ learning in pre-COVID and during COVID condition. This study later explored various literatures to gather experiences from other universities across the globe and by analysing all findings including academic experiences finally developed constructive recommendations for improvement. It is found that the current form of online mode of teaching has room to improve further as one segment of students finds it challenging and some others like a few approaches. It is also found that the online infrastructure, staff skills to innovate new unit designs, and motivating students are the other challenging areas. Therefore, a new teaching and learning framework is required to overcome all the challenges for future learning.

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Section: Globally Observed Covid-19 Challenges On Educationmentioning

confidence: 90%

Exploring Teaching and Learning Experience during COVID-19 Pandemic in Engineering Education

Arif

Shafiullah

2022

Sustainability

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“…Karahoca and Zaripova et al [1] aimed to investigate engineering university students' perceptions regarding distance learning during pandemic. They emphasized that students were able to access their courses using smart devices and satisfied with distant learning as they have not fallen behind in their studies.…”

Section: Literature Reviewmentioning

confidence: 99%

Ensemble Machine Learning Model for University Students’ Risk Prediction and Assessment of Cognitive Learning Outcomes

Mary.T¹,

J²

2023

IJIET

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One of the biggest challenges in higher educational institutions is to avoid students’ failures. Globally student dropout is a serious issue. Risk of dropouts can be identified at an earlier stage using machine learning classifiers, as they have gained more popularity in both academia and industry. The research team suggests that early prediction facilitates educators and higher education administrators to take necessary measures to prevent dropouts. Data for the research were collected from 530 Indian students when they were engaged in online learning during pandemic crisis. This research work involves two phases. In first phase, hybrid ensemble strategy is focused that integrates two powerful machine learning algorithms namely Random Forest (RF) and eXtreme Gradient Boosting (XGBoost) for early at-risk prediction. The result is a fast procedure for classification of at-risk students which is competitive in accuracy and highly robust. Prediction models are developed using ensemble learning, furthermore ensemble models are combined into a single meta-model, which provides best outcomes to enable higher education institutions for predictive analysis. Moreover, it correctly classified students’ at-risk regarding accuracy, precision, recall and F1-score with values of 93%, 91.52%, 96.42% and 93.91% respectively. In second phase, prediction model is deployed by creating a web application using. Net framework to sense students’ sentiments using Azure cognitive services text analytics (Application Programming Interface) API for detecting cognitive behavioral outcomes in online learning environment.

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“…In contrast, some studies [4] point out the relative advantage of distance forms of education in the more flexible and easier access to the desired number and specialization of courses, the technological sophistication of quality online platforms and the ability to use the course whenever they want. In this context, another study [5] further highlights the popularity of smart devices to record, share and watch lessons at any time, it is particularly positive about the Zoom Video Conferencing app, which was effectively used by students to communicate and gain knowledge with the possibility of learning anytime, anywhere.…”

Section: Literature Reviewmentioning

confidence: 99%

Perception of Selected Aspects of Online Learning by Czech Higher Education Students

Krelová¹,

Berková²,

Krpálek³

et al. 2022

Int. J. Eng. Ped.

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The study is based on an analysis of real educational processes in the period 2020-2021, when the most significant pandemic waves of Covid-19 were recorded in the Czech Republic. In relation to this, the study aims to identify the views of 968 students on the changed conditions of education and the perception of selected aspects of the transition to online learning by respondents from two higher education institutions in the Czech Republic, the first of which is focused on humanities and the second specializes in economics studies. The research is aimed at discovering students’ attitudes towards the form of distance education forced on them by the relevant circumstances, the use of individual components of distance education to support teaching originally designed for the in-person form, the level and effectiveness of the use of information technologies in online learning and the potential of hybrid learning. For a greater degree of analyticity, a combined research model based on both quantitative and qualitative research has been chosen. Aspects of online learning that could be employed as complementary tools in the full-time conventional study mode have been identified. Students of economics can better visualize the inclusion of online learning in the full-time conventional study mode. Master level students are critical of online learning. The results have been used to design and empirically validate appropriate learning strategies with reflection on current student needs.

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During the Covid-19 Pandemic, Students' Opinions on Distance Education in Department of Engineering

Cited by 9 publications

References 16 publications

Exploring Teaching and Learning Experience during COVID-19 Pandemic in Engineering Education

Exploring Teaching and Learning Experience during COVID-19 Pandemic in Engineering Education

Ensemble Machine Learning Model for University Students’ Risk Prediction and Assessment of Cognitive Learning Outcomes

Perception of Selected Aspects of Online Learning by Czech Higher Education Students

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