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The application of massive open online courses (MOOCs) helps integrate sustainable development goals (SDGs) into architectural curricula. The essence of MOOC development is building an education platform that promotes the sharing and continuing of global education resources.

This study establishes a four-dimensional evaluation model based on the four characteristics of MOOCs. The quadrilateral area evaluation method is used to create an evaluation radar chart to comprehensively evaluate satisfaction and demand in the traditional teaching model of architectural technology. This study discusses whether the curriculum is suitable for the development of MOOCs and how to optimize the sustainable pedagogical mode according to its characteristics to meet future teaching needs and realize the sustainable development of education.

Satisfaction evaluation found that current education is not open enough from the students' perspective; therefore, MOOCs enhance students' participation and significantly reduce future learning costs. Through demand evaluation, it was found that both teachers and students believed that the lack of direct and effective communication between them and the difficulty in ensuring the learning effect were problems that must be addressed in MOOCs.

This study focused on the sustainability of MOOCs in curriculum development. It emphasizes the combination of MOOCs' teaching modes and the course itself and provides specific guidance and suggestions for improving the course. It uses an evaluation method for objective analysis and visualization.

Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation process to ensure remedial actions. This study aims to conduct an experimental research to detect anomalies in the evaluation methods.

Experimental research is conducted with scientific approach and design. The researchers categorized anomaly into three categories, namely, an anomaly in criteria assessment, subject anomaly and anomaly in subject marks allocation. The different anomaly detection algorithms are used to educate data through the software R, and the results are summarized in the tables.

The data points occurring in all algorithms are finally detected as an anomaly. The anomaly identifies the data points that deviate from the data set’s normal behavior. The subject which is consistently identified as anomalous by the different techniques is marked as an anomaly in evaluation. After identification, one can drill down to more details into the title of anomalies in the evaluation criteria.

This paper proposes an analytical model for the course evaluation process and demonstrates the use of actionable analytics to detect anomalies in the evaluation process.

As global issues such as climate change, economic growth, social equality and the wealth gap are widely discussed, education for sustainable development (ESD) allows every human being to acquire the knowledge, skills, attitudes and values necessary to shape a sustainable future. It also requires participatory teaching and learning methods that motivate and empower learners to change their behavior and take action for sustainable development. Teachers have begun rating pupils based on peer assessment for open evaluation. Peer assessment enables students to transition from passive to active feedback recipients. The assessors improve critical thinking and encourage introspection, resulting in more significant recommendations. However, the quality of peer assessment is variable, resulting in reviewers not recognizing the remarks of other reviewers, therefore the benefits of peer assessment cannot be fulfilled. In the past, researchers frequently employed post-event questionnaires to examine the effects of peer assessment on learning effectiveness, which did not accurately reflect the quality of peer assessment in real time.

This study employs a multi-label model and develops a self-feedback system in order to use the AIOLPA system in the classroom to enhance students' learning efficacy and the validity of peer assessment.

The research findings indicate that the better peer assessment through the rapid feedback system, for the evaluator, encourages more self-reflection and attempts to provide more ideas, so bringing the peer rating closer to the instructor rating and assisting the evaluator. Improve self-evaluation and critical thinking for the evaluator, peers make suggestions and comments to help improve the work and support the growth of students' learning effectiveness, which can lead to more suggestions and an increase in the work’s quality.

ESD consequently promotes competencies like critical thinking, imagining future scenarios and making decisions in a collaborative way. This study builds an online peer assessment system with a self-feedback mechanism capable of classifying peer comments, comparing them with scores in a consistent manner and providing prompt feedback to critics.

This study aims to gain insights into how students perceive online examination practices and evaluation, as well as identify the key factors that impact their intentions toward online exams.

This empirical study conducted in India utilized an online survey method between May 24 and June 14, 2022. The data were collected from 712 undergraduate and postgraduate students through a Google Docs questionnaire. Descriptive analysis, exploratory factor analysis (EFA), regression and reliability analysis were conducted to analyze the data.

There are many studies related to the adoption of online learning. However, there are limited studies that explore the adoption and acceptance of online examinations and evaluations. This paper intends to fill this gap and tries to highlight important factors influencing online examination usage by the students. Five important factors emerged in the study include “pedagogy, validity, reliability,” “practicality,” “security,” “facilitating condition” and “intention,” The study concludes that taking tests online is preferred for several reasons, including the perceived increased dependability of grades and the decreased cost, time and effort associated with taking exams.

This research explores students' perceptions of learning management systems (LMS)-based online exams and provides insights for students to better prepare and adapt. It assists policymakers in developing fair assessment policies and improving LMS platforms. The study contributes to the theoretical understanding of e-learning and calls for further research to enhance the effectiveness of online exams. It identifies gaps in existing literature and recommends larger sample sizes, broader representation, longitudinal data collection and conversational methods for future research.

This study shows increasing research on e-learning and online examinations, mostly using quantitative methods. The important variables for understanding students' perceptions of online exams are “pedagogy, validity, reliability,” “practicality,” “security,” “facilitating condition” and “intention.” Concerns raised include validity, fairness and security. Electronic exams are more suitable for formative evaluation, and validity, reliability, security and adaptability are key pillars for successful online testing.

The purpose of this study was constructed a behavioral observation scale for avoiding food waste from the point of view of Chinese cuisine, used as an evaluation tool to examine food waste in the process of food preparation for hospitality students in Taiwan.

The status of food handling in the preparation process was understood through a literature review and interviews. In addition, the indicators that may cause food waste behaviors were established, and the observation and self-evaluation scales of food waste behaviors in the preparation process were developed.

Avoiding water waste, removing excessive edible parts, avoiding waste on seasonings, avoiding cooking for too long and avoiding water stains in the cleaning process were considered by both the observers and the students as items for improvement in the cooking process. The results of this study will help in understanding the intervention in the teaching practice of avoiding students’ food waste behaviors.

This study can only be based on the test results of the current observation behaviors. Meanwhile, many factors need to be taken into consideration, such as the differences in the amount of knowledge students have about food waste, the differences in preparation techniques, and other different factors, which may lead to differences in the research results.

The behavioral observation and self-evaluation behavior scales of “exploring food waste behaviors in the preparation process” were developed and implemented for the current status. The differences between the results of the observation scale and the self-evaluation scale were compared. In addition, the behaviors that may cause students’ food waste were pointed out. Then, the direction of the teaching content was formulated, and the curriculum plan integrating the content of avoiding food waste into teaching was evaluated. Furthermore, the scales can be applied to kitchen staff handling food materials to understand the current situation of their food handling, which can be used as a driving tool for restaurants to reduce food waste.

This study aims to discover how domain familiarity and language affect the cognitive load and the strategies applied for the evaluation of search engine results pages (SERP).

This study used an experimental research design. The pattern of the experiment was based upon repeated measures design. Each student was given four SERPs varying in two dimensions: language and content. The criteria of students to decide on the three best links within the SERP, the reasoning behind their selection, and their perceived cognitive load of the given task were the repeated measures collected from each participant.

The evaluation criteria changed according to the language and task type. The cognitive load was reported higher when the content was presented in English or when the content was academic. Regarding the search strategies, a majority of students trusted familiar sources or relied on keywords they found in the short description of the links. A qualitative analysis showed that students can be grouped into different types according to the reasons they stated for their choices. Source seeker, keyword seeker and specific information seeker were the most common types observed.

This study has an international scope with regard to data collection. Moreover, the tasks and findings contribute to the literature on information literacy.

This paper aims to investigate the relationship between student emotions, professors' performance and course ratings and difficulty.

Natural language processing models are used to extract six basic emotions and several categories of professors' harmful performance from nearly one million student reviews randomly selected from the website ratemyprofessors.com. These features are used in regression analysis to analyse their relationship with numerical ratings of course quality and course difficulty.

Negative emotions and bad performance by professors are detected more often for low-rated courses and courses perceived as more difficult by students. Positive emotions are seen for highly rated and less challenging courses.

This paper shows that natural language processing tools can be used to enhance and strengthen the quality assurance processes at universities. The proposed methods can improve the often-contested student evaluation of teaching practices, help students make better and more informed choices about their courses and assist instructors to better tailor their teaching approaches and create a more positive learning environment for their students.

This paper presents a novel analysis of how student emotions and poor performance by professors, derived automatically from teacher evaluations by students, affect course ratings. Results also lead to a novel hypothesis that the student–course emotional match or student tolerance of bad behaviour by professors can affect the performance of students and their chances of completing their degree.

This paper presents a case study for the pilot of a peer-led service model that is centered on fostering student leadership, collaboration and advocacy. The authors, who serve as advisors to the program, discuss the Library's transition to this peer-led model for reference support, outreach, programming and campus engagement.

This case study examines the development and implementation of a new peer-led service at a mid-size public university aimed at centering student success, belonging and empowerment. Authors share practices, strategies and goals for training, onboarding and professional development with emphasis on student advocacy, leadership and retention in the program.

The authors found that developing the structures and opportunities to foster student-led initiatives and efforts for student success, belonging and engagement has helped the library better connect and engage with diverse student communities on campus.

Findings of this study may be limited at the time this case study is written due to it being a new and developing library student program for reference, outreach and programming.

The peer-led service model for reference and student engagement presented in this article serves as a case study that may be applicable for those who wish to imagine and develop a student-centered library program at their institution.

This case study may provide an alternative approach useful to those who wish to reimagine and innovate library student programs at their institutions.

Although there are many peer-led initiatives in academic libraries for outreach and programming, this program explores the approach of fostering student leadership and advocacy within library student roles to lead and facilitate library efforts for campus engagement with structured guidance and support from librarian advisors.

The purpose of this study is to propose a framework for the convergence of maturity model and education and evaluation in accounting.

The present research was conducted in two phases. In the first phase, to determine the indicators of convergence of the maturity model and education and evaluation in accounting, a Meta-Synthesis method was used. The conceptual model includes two dimensions of “Teaching and learning processes” and “Evaluation methods"; five levels of initial, repeatable, defined, managed and optimized; and a total number of 35 indicators. In the second phase, a questionnaire was developed, and academics as accounting faculty members in Iranian public universities were employed to fill out the questionnaire electronically and present a final framework. Having received the questionnaires, 66 questionnaires were analyzed statistically.

The results showed that the two dimensions of “Teaching and learning processes” and “Evaluation methods” considering initial, repeatable, defined, managed and optimized levels include 35 indicators, which form a framework for the convergence of maturity model and education and evaluation in accounting. The results show that both dimensions have positive and significant regression path coefficients in the convergence model. Moreover, the dimension of teaching and learning processes has the highest regression path coefficient indicating a greater impact on the convergence model. Besides, all five levels have positive and significant regression path coefficients with dimensions. Finally, in this study, all indicators were prioritized according to five levels.

Due to the success of maturity models and the urgent developments that require transformative improvements in accounting education, maturity models can respond to the challenges associated with education and learning in accounting. Thus, conceiving an image of the convergence of maturity model, education and evaluation in accounting seems imperative which has been scarcely investigated previously.

The emergence of the COVID-19 pandemic changed the way in which education was delivered in early 2020, and the impacts of these changes continue to be questionable. The aims of this study were to evaluate: (1) the results obtained by students of the Dentistry course in the progress test carried out both before and after the pandemic, (2) the results obtained by a specific group of students who took the test in 2019–2022, and compare their results and (3) subjects that showed a reduction in the percentage of correct answers when the two tests were compared.

The progress test consisting of 100 multiple choice questions was applied before and after the pandemic to all students in the Dentistry course. The analyses were performed using the IBM SPSS for Statistics v.26 software program. The level of significance of 5% was adopted (<0.05).

The test was applied to 320 students in 2019 and to 272 in 2022, of whom the sample of this study was composed. The mean score values in 2019 (M = 49.10; SD = 12.03) were significantly (p = 0.026) higher than those in the year 2022 (M = 46.97; SD = 12.15), with the disciplines in the area of specific knowledge showing a greater drop in the percentage of correct answers by students. This study showed that the emergency remote education had a negative effect on the academic performance of students, based on the progress testing as an evaluation method.

Many studies that assessed the impacts of the pandemic on teaching were focused on the opinions of students. However, the great advantage of our study was the use of a theoretical assessment tool to verify student performance. The post-pandemic landscape beckons for comprehensive inquiries into these domains. This type of research would be valuable for gathering evidence relative to the performance of students after the emergency remote education.