Let them choose: Optional assignments and online learning patterns as predictors of success in online general chemistry courses

Feldman-Maggor, Yael; Blonder, Ron; Tuvi-Arad, Inbal

doi:10.1016/j.iheduc.2022.100867

Cited by 21 publications

(16 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some researchers have tried to develop assisted adaptive apps to test the efectiveness of teaching. Other studies have attempted to add testing units to the teaching system to obtain evaluation results between teachers and students in both directions [11][12][13]. Some studies have also proposed to integrate parameters such as students' postclass grades, teachers' performance in class, and student's classroom performance into neural networks students to obtain trend lines of teaching effectiveness factors as an evaluation criterion.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Neural Network for the Online Course Quality Assessment System

Bai

Yong-guo

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

Under the influence of COVID-19, online office and online education has ushered in a golden period of development. The teaching quality of online education has been a controversial issue. Our study takes online course teaching quality assessment as the starting point, explores the influencing factors of online course quality assessment with online courses as the research object, and analyzes the latest research proposal for an online course quality index. To make the online course quality assessment more intelligent, we propose an online course quality assessment method based on a fuzzy neural network. The method uses fuzzy rules as the baseline and adds a TSK perception mechanism to expand the perception domain of the fuzzy neural network and improve the course quality index prediction accuracy. At the input side of the fuzzy neural network, we preclassify the online course data into four parts, and each part of the data represents a different assessment domain. Due to the large data cost, we expanded the collective amount of data using data augmentation methods. In addition, we parse the structure of the fuzzy neural network hierarchy and introduce the construction and role of the TSK perception mechanism in the fuzzy rules. An optimal learning strategy is proposed in the fuzzy neural network training. Finally, in the experimental session, we verify the effectiveness of data augmentation and explore the distribution of course quality assessment weights. In the comparison of the model prediction results with the actual assessment results, our method achieves an excellent matching rate, which proves the high efficiency of our method in the online course quality assessment system.

show abstract

Section: Introductionmentioning

confidence: 99%

Fuzzy Neural Network for the Online Course Quality Assessment System

Bai

Yong-guo

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…A connection emerged between the lecturers’ satisfaction and better student performance and a correlation between the lecturers’ and the students’ satisfaction with online courses. Various factors may affect student satisfaction, including lecturer-student interaction, learner-content interaction [ 58 ], and self-efficacy in using the internet [ 59 , 60 ]. Students also mentioned convenience as a reason for their satisfaction with an online course, whereas the lack of interaction had the greatest effect on their dissatisfaction [ 61 ].…”

Section: Discussionmentioning

confidence: 99%

What can be learned from lecturers’ knowledge and self-efficacy for online teaching during the Covid-19 pandemic to promote online teaching in higher education

2022

Self Cite

View full text Add to dashboard Cite

The experience of graduate degree lecturers in the natural sciences when they switched to online teaching during the Covid-19 pandemic is described. The shift to online teaching throughout the pandemic provided an opportunity to evaluate how lecturers integrate technology into their teaching and what they need to improve their remote teaching. This study used a twofold perspective of TPACK (Technological Pedagogical Content Knowledge) and self-efficacy in online education. Its data were derived from pre-and post-questionnaires, comprising closed and open-ended questions, given at the start and end of the semester. We found that lecturers focused on learning and applying technological and techno-pedagogical knowledge but paid less attention to the integration of three components: technology, pedagogy, and scientific content. Although no statistically significant differences in lecturers’ perceived self-efficacy was found between the start and the end of the semester, at the end of the semester we found a statistically significant correlation between the variables involved in building self-efficacy in online teaching: (1) satisfaction with online teaching and the belief that (2) technology promotes teaching, student interactions, participation, and engagement. Our results enabled us to identify the knowledge aspects that lecturers implemented initiatively and to better understand what aspects required more professional development training. In addition, the results emphasized the importance of developing the lecturers’ self-efficacy for online teaching. These insights can help to improve and enhance online teaching in higher education.

show abstract

“…Additionally, the teachers were exposed to lectures of contemporary research in computational chemistry in order to connect chemistry teaching to contemporary research and cutting-edge knowledge as well as develop their own contemporary content knowledge in CC. All the video recorded lectures in the course were linked to a short quiz to encourage the participants to actively learn . In the second section, the teachers experienced hands-on workshops in using Avogadro software (the complete exercises are presented in the SI).…”

Section: Methodsmentioning

confidence: 99%

“…All the video recorded lectures in the course were linked to a short quiz to encourage the participants to actively learn. 56 In the second section, the teachers experienced hands-on workshops in using Avogadro software (the complete exercises are presented in the SI). The workshop exercises were conducted remotely via a Zoom meeting.…”

Section: Course Structure and Contentmentioning

confidence: 99%

A Computational Chemistry Course for Teachers: From Research Laboratories to High-School Chemistry Teaching

Traube,

Blonder

2023

J. Chem. Educ.

Self Cite

View full text Add to dashboard Cite

Computational chemistry (CC) is an important and essential area within chemical sciences. Over the years, CC has developed rapidly and played a significant role in chemistry research. In addition to the centrality of CC in the chemical sciences, teachers and students should be exposed to contemporary research for many reasons. These reasons include elevating student motivation to study science and engineering and increasing student interest in scientifically oriented careers. For teachers, contemporary research can trigger their professional development and keep them up to date with current research in their teaching field. However, the integration of CC tools within chemistry education can be challenging for both teachers and students. Here we describe a course on CC for high-school teachers. The goal was to introduce the teachers to contemporary CC contents and tools and motivate them to utilize their knowledge in the teaching of chemistry. We describe the course structure and contents that included lectures, hands-on workshop exercises, and assignments. The rationale behind each part of the course is detailed and the workshop instructions that were conducted using the free Avogadro software are completely presented in the Supporting Information. The course evaluation indicated that teachers improved their contemporary CC content knowledge and were satisfied with how the course contributed to their chemistry teaching.

show abstract

Let them choose: Optional assignments and online learning patterns as predictors of success in online general chemistry courses

Cited by 21 publications

References 66 publications

Fuzzy Neural Network for the Online Course Quality Assessment System

Fuzzy Neural Network for the Online Course Quality Assessment System

What can be learned from lecturers’ knowledge and self-efficacy for online teaching during the Covid-19 pandemic to promote online teaching in higher education

A Computational Chemistry Course for Teachers: From Research Laboratories to High-School Chemistry Teaching

Contact Info

Product

Resources

About