Electronic portfolios (e-portfolios) have a positive impact on the learning process in a broad range of educational sectors and on learners of all ages. Yet because most e-portfolio-related studies are about their implementation in higher education, this type of research is less usual in the early childhood context, and there is no available research for Greek schools. This study aims to investigate the impact of e-portfolios on learning in a Greek primary school and to provide a resource regarding the educational benefits of e-portfolio in primary education. To do that, it employs the qualitative naturalistic method to collect data, along with mixed methods which were used to achieve triangulation and strengthen confidence in the outcomes. Participants in the research were fourteen 8-year-old pupils, and one of the researchers was their regular teacher. Data evaluation revealed that the e-portfolio added value in pupils’ learning, acted as a medium to involve parents, promoted pupils’ self-esteem, and was acknowledged as a valuable assessment tool and a challenge for the school community. Based on the experience of the e-portfolio implementation, the authors provide some suggestions that would possibly help researchers and primary school teachers adopt and develop e-portfolio systems in their particular settings.

An online Moodle Workshop was evaluated for peer assessment effectiveness. A quasi-experiment was designed using a Seminar in Professionalism course taught in face-to-face mode to undergraduate students across two campuses. The first goal was to determine if Moodle Workshop awarded a fair peer grader grade. The second objective was to estimate if students were consistent and reliable in performing their peer assessments. Statistical techniques were used to answer the research hypotheses. Although Workshop Moodle did not have a built-in measure for peer assessment validity, t-tests and reliability estimates were calculated to demonstrate that the grades were consistent with what faculty expected. Implications were asserted to improve teaching and recommendations were provided to enhance Moodle.

Pair programming is a collaborative programming practice that places participants in dyads, working in tandem at one computer to complete programming assignments. Pair programming studies with Computer Science (CS) and Software Engineering (SE) majors have identified benefits such as technical productivity, program/design quality, academic performance, and increased satisfaction for their participants. In this paper, pair programming is studied with Management Information Systems (MIS) majors, who (unlike CS and SE majors taking several programming courses) typically take only one programming course and often struggle to develop advanced programming skills within that single course. The researchers conducted two pair programming experiments in an introductory software development course for MIS majors over three semesters to determine if pair programming could enhance learning for MIS students. The program results, researchers’ direct observations, and participants’ responses to a survey questionnaire were analyzed after each experiment. The results indicate that pair programming appears to be beneficial to MIS students’ technical productivity and program design quality, specifically the ability to create programs using high-level concepts. Additionally, results confirmed increased student satisfaction and reduced frustration, as the pairs worked collaboratively to produce a program while actively communicating and enjoying the process.

Aim/Purpose: To examine the early perceptions (acceptability) and usability of EASEL (Education through Application-Supported Experiential Learning), a mobile platform that delivers reflection prompts and content before, during, and after an experiential learning activity. Background: Experiential learning is an active learning approach in which students learn by doing and by reflecting on the experience. This approach to teaching is often used in disciplines such as humanities, business, and medicine. Reflection before, during, and after an experience allows the student to analyze what they learn and why it is important, which is vital in helping them to understand the relevance of the experience. A just-in-time tool (EASEL) was needed to facilitate this. Methodology: To inform the development of a mobile application that facilitates real-time guided reflection and to determine the relevant feature set, we conducted a needs analysis with both students and faculty members. Data collected during this stage of the evaluation helped guide the creation of a prototype. The user experience of the prototype and interface interactions were evaluated during the usability phase of the evaluation study. Contribution: Both the needs analysis and usability assessment provided justification for continued development of EASEL as well as insight that guides current development. Findings: The interaction design of EASEL is understandable and usable. Both students and teachers value an application that facilitates real-time guided reflection. Recommendations for Practitioners: The use of a system such as EASEL can leverage time and location-based services to support students in field experiences. This technology aligns with evidence that guided reflection provides opportunities for metacognition. Recommendation for Researchers: Iterative prototyping, testing, and refinement can lead to a deliberate and effective app development process. Impact on Society: The EASEL platform leverages inherent functionality of mobile devices, such as GPS and persistent network connectivity, to adapt reflection tasks based on lo-cation or time. Students using EASEL will engage in guided reflection, which leads to metacognition and can help instructors scaffold learning Future Research: We will continue to advance the application through iterative testing and development. When ready, the application will be vetted in larger studies across varied disciplines and contexts.

Aim/Purpose: Improving public schools is a focus of federal legislation in the United States with much of the burden placed on principals. However, preparing principals for this task has proven elusive despite many changes in programming by institutions of higher learning. Emerging technologies that rely on augmented and virtual realities are posited to be powerful pedagogical tools for closing this gap. Background: This study investigated the effects of immersive simulation technologies on principals’ self-efficacy after treatment and the perceived significance of the design of the immersive simulation experience as an effective tool for adult learners. Methodology: The investigator employed a multiple-methods study that relied on a purposive sample of graduate students enrolled in educational leadership programs at two small universities in the southeastern United States. Participants completed a two-hour module of immersive simulation designed to facilitate transfer of knowledge to skills thereby increasing their self-efficacy. Contribution: This paper contributes to a small body of literature that examines the use of immersive simulation to prepare aspiring principals. Findings: The findings indicate moderate effect sizes in changes in self-efficacy, positive attitudes toward immersive simulation as a pedagogical tool, and significance in the design of immersive simulation modules. This suggests that immersive simulation, when properly designed, aids principals in taking action to improve schools. Recommendations for Practitioners: Educational leadership programs might consider the use of immersive simulations to enhance principals’ ability to meet the complex demands of leading in the 21st century. Impact on Society: Principals may be more adept at improving schools if preparation programs provided consistent opportunities to engage in immersive simulations. Future Research: Future research should be conducted with larger sample sizes and longitudinally to determine the effectiveness of this treatment.

Aim/Purpose: Although many computer science measures have been proposed, visualizing individual students’ capabilities is difficult, as those measures often rely on specific tools and methods or are not graded. To solve these problems, we propose a rubric for measuring and visualizing the effects of learning computer programming for elementary school students enrolled in computer science education (CSE), which is independent of the programming language being used. Background: In this research, we proposed a rubric based on existing CSE standards and criteria having a programming education-learning goal. We then applied this rubric to actual lessons to visualize the educational effects. Methodology: The proposed new rubric for teaching computer programming, based on existing standards and criteria, was applied to fourth- and sixth-grade students in Japan. We assessed which skills were cultivated through quizzes before and after the teaching. Contribution: This paper contributes on how to make and utilize a rubric for programming education in computer science. We evaluated and visualized the proposed rubric’s learning effects on children and found that our proposed rubrics are independent of any particular method or tool. Findings: The results of this survey are twofold: (1) we proposed a rubric of programming education in computer science, independent of the programming tools used and (2) we succeeded in visualizing students’ learning stages by applying the proposed rubric to programming education conducted in a Japanese elementary school. Recommendations for Practitioners: Evaluating educational effects in CSE is important. In particular, graded assessments of learner abilities can reveal individual characteristics. This research is useful for assessing CSE because it focuses specifically on programming education. Recommendation for Researchers: The rubric’s suggestions and quality improvements in CSE help learners assess their learning progress and will clarify the cultivated computer science skills. Impact on Society: This research evaluates CSE based on a rubric in the programming education field. Future Research: Future work is needed to improve the proposed rubric’s quality and relevance. Also, this rubric should be applied to many classes to increase the number of evaluations and analyses.

Aim/Purpose: The current study was conducted to investigate the students’ perceived satisfaction with the use of a semantic-based online laboratory, which provides students with a search mechanism for laboratory resources, such as instruments and devices. Background: The increasing popularity of using online teaching labs, as an important element of experiential learning in STEM education, is because they represent a collection of integrated tools that allow students and teachers to interact and work collaboratively, whereas they provide an enriched learning content delivery mechanism. Moreover, several research studies have proposed various approaches for online teaching laboratories. However, there are hardly any studies that examine the student satisfaction provided by online laboratories based on students’ experiential learning. Methodology: To measure the effectiveness of the laboratory, we performed a case study in a Computer Fundamentals online course in which undergraduate students were able to manage devices and instruments remotely. Participants were a sample of 50 third semester students of Bachelor’s degree in Information Technology Administration who were divided in experimental and control groups (online laboratory vs. traditional manner). Given a laboratory assignment, students were able to carry out the management of devices and instruments through a LabView virtual environment and web services. The data of the experiment were collected through two questionnaires from both groups. The first is a system usability score (SUS) questionnaire concerning lab usability and the second one students’ cognitive load. Contribution: The results of the study showed a high correlation between usability and cognitive load-satisfaction of students who used the online teaching laboratory compared to the students who did not use it. Findings: On the one hand, the online laboratory provided students with an easy way to share and deploy instruments and devices, thus enhancing system usability. On the other hand, it offered important facilities which enabled students to customize the search for instruments and devices, which certainly had a positive impact on the relationship between cognitive load and satisfaction. Recommendations for Practitioners: In this work we propose an intuitive laboratory interface as well as easiness to use but challenging and capable of providing similar experiences to the traditional laboratory. Recommendation for Researchers: This study is one of the first to analyze the cognitive load-satisfaction relationship and compare it with usability scores. Impact on Society: Our analyses make an important contribution to the literature by suggesting a correlation analysis comparing the results of experimental and control groups that participated in this research work, in terms of usability and cognitive load-satisfaction. Future Research: Future work will also investigate other methodological aspects of instructional design with the aim to improve personalized learning and reinforce collaborative experiences, as well as to deal with problems related to laboratory access, such as authentication, scheduling, and interoperability.

Aim/Purpose: This study reports the outcome of how a first pilot semester introductory programming course was designed to provide tangible evidence in support of the concept of Student Ownership of Learning (SOL) and how the outcomes of this programming course facilitate effective student learning. Background: Many instructors want to create or redesign their courses to strengthen the relationship between teaching and learning; however, the researchers of this study believe that the concept of Student Ownership of Learning (SOL) connects to student engagement and achievement in the classroom setting. The researchers redesigned the introductory programming course to include valuable teaching methods to increase Student Ownership of Learning and constructive approaches such as making students design an authentic mobile app project as individuals, partners, or within teams. The high quality of students’ projects positioned them as consultants to the university IT department. Methodology: This paper employs a case study design to construct a qualitative research method as it relates to the phenomenon of the study’s goals and lived experiences of students in the redesigned introductory programming course. The redesigned course was marketed to students as a new course with detailed description and elements that were different from the traditional computer science introductory programming course requirement. The redesigned introductory programming course was offered in two sections: one section with 14 registered students and the other section with 15 registered students. One faculty member instructed both sections of the course. A total of 29 students signed up for the newly redesigned introductory programming course, more than in previous semesters, but two students dropped out within the first two weeks of the redesigned course making a total of 27 students. The redesigned coursework was divided into two parts of the semester. The first part of the semester detailed description and elements of the coursework including a redesigned approach with preparation for class, a quiz, and doing homework in class, which gives students control of decisions whenever possible; and working with each other, either with a partner or in a team. The second part of the semester focuses on students designing a non-trivial working mobile app and presenting their developing mobile app at a significant public competition at the end of the semester. Students developed significantly complex mobile apps and incorporated more complex functionality in their apps. Both Management Information System (MIS) major students and Computer Science major students were in the same course despite the fact that MIS students had never taken a programming course before; however, the Computer Science students had taken at least one course of programming. Contribution: This study provides a practical guide for faculty members in Information Technology programs and other faculty members in non-Computer Science programs to create or redesign an introductory course that increases student engagement and achievement in the classroom based on the concept of Student Ownership of Learning (SOL). This study also deepens the discussion in curriculum and instruction on the value to explore issues that departments or programs should consider when establishing coursework or academic programs. Findings: This study found two goals evidently in support to increase Student Ownership of Learning (SOL). The first goal (Increase their ownership of learning SOL) showed that students found value in the course contents and took control of their learning; therefore, the faculty no longer had to point out how important different programming concepts were. The students recognized their own learning gap and were excited when shown a programming concept that addressed the gap. For example, student comments were met with “boy, we can really use this in our app” instead of comments about how complex they were. The coursework produced a desired outcome for students as they would get the knowledge needed to make the best app that they could. The second goal (Develop a positive attitude toward the course) showed positive results as students developed a more positive attitude towards the course. Student actions in the classroom strongly reflected a positive attitude. Attendance was almost 100% during the semester even though no points for attendance were given. Further evidence of Student Ownership of Learning and self-identity was students’ extensive use of the terminology and concept of the course when talking to others, especially during the public competition. Students were also incorporating their learning into their identities. For example, teams became known by their app such as the Game team, the Recipe team, and the Parking team. One team even made team t-shirts. Another exciting reflection of the Student Ownership of Learning which occurred was the learning students did by themselves. Recommendations for Practitioners: Practitioners can share best practices with faculty in different departments, programs, universities, and educational consultants to cultivate the best solution for Student Ownership of Learning based on student engagement and achievement in the classroom setting. Recommendation for Researchers: Researchers can explore different perspectives with scholars and practitioners in various disciplinary fields of study to create or redesign courses and programs to reflect Student Ownership of Learning (SOL). Impact on Society: Student Ownership of Learning is relevant for faculty and universities to incorporate in the creation or redesigning of coursework in academic programs. Readers can gain an understanding that student engagement and achievement are two important drivers of Student Ownership of Learning (SOL) in the classroom setting. Future Research: Practitioners and researchers could follow-up in the future with a study to provide more understanding and updated research information from different research samples and hypotheses on Student Ownership of Learning (SOL).

Aim/Purpose: This study aimed to reveal the effect of the previous Internet-based education (IBE) experiences of the students’ readiness, attitude, and self-control / self-management variables towards the e-learning process, and also to determine their opinions. Background: The institutions have made efforts to ensure the continuity of education through their learning management systems and the necessity of addressing the e-learning process from the perspective of students once again showed itself as an undeniable fact. Accordingly, the necessity to consider holistically the variables of readiness, attitude, and self-control/self-management, which affect students’ adaptation to e-learning process, has once again emerged based on the relevant literature. Methodology: This research based on the simultaneous mixed method considering the previous IBE experiences of 75 Computer Education and Instructional Technology (CEIT) students taking part in the study in Turkey. The quantitative results of the study were analyzed based on the single-group pretest-posttest weak experimental design. Qualitative results were obtained through the structured interview form and set an example for the case study. Contribution: The results showed that regardless of students’ previous Internet-based education (IBE) experience, it is seen that increasing and continuous experience has a significant effect on the readiness, attitude and self-control / self-management variables towards the e-learning process. The main contribution of experimental results showed that IBE experience is effective on individuals’ perceptions of internet self-efficacy, and has an impact on the self-learning skills of individuals. In addition to this, the e-learning experience has an impact on individuals’ self-evaluation. It is also seen that the certificate presented to learners in the e-learning environment has a positive effect on students’ attitudes towards e-learning processes. Finally, the experiences of e-learning processes, the methods used to transfer the content in the learning environment, the motivation and feedback provided to the learner also support the significant difference obtained in terms of readiness, attitude and self-control / self-management. Findings: After the findings were analyzed holistically in depth, it has been observed that; if the contents offered to students in e-learning environments support their professional development, in this case, their attitudes, readiness (excluding the sub-dimension of learner control), and self-control/self-management skills for these environments differ significantly in the posttest. It is also among the results that students having previous IBE experience have not higher awareness levels on online communication self-efficacy, technology use self-efficacy, readiness for e-learning, e-learning predisposition, self-reinforcement, self-control management, although significantly found. The findings regarding the effectiveness of the experimental process are as follows: Although it is possible for the students having previous IBE experience to use these experiences within the course for their personal development, it has been seen that the observed differences regarding students’ readiness, attitude, and self-control/self-management towards e-learning processes arise from the experimental operation. Recommendations for Practitioners: It is recommended for the policy-makers and practitioners that while e-learning platforms were designing, using different methods for delivering the content is as important as making the interaction meaningful and sustainable. In addition to this, to develop a positive attitude it is recommended that individuals’ participation of an e-learning platform should be supported with a certificate. Recommendation for Researchers: Researchers should test the obtained results by a well-structured e-learning platform with their recorded activities on the platform (e.g. in which section was used mostly by a learner etc.). Hence, the impact of IBE experiences might be discussed in an up level framework. Impact on Society: Actually, this study is based on a mix design and the results were also meaningful especially considering the implacable global pandemic. It is clearly understood by this process that e-learning is very important. In line with this, to support the e-learning process (e.g. with the method while delivering the content, well-structured feedback, motivation strategies etc.) and make it sustainable, the increasing of individual’s readiness, attitude, and self-control through the IBE would be indispensable. Future Research: Future studies might focus on the longitudinal methods. It is worth to find out how the students experiences affect the sustainability of the course content, and what should the program developer make to improve their course content in line with the findings of longitudinal studies.

Aim/Purpose: This mixed-methods study aims to examine factors influencing academicians’ intentions to continue using AI-based chatbots by integrating the Task-Technology Fit (TTF) model and social network characteristics. Background: AI-powered chatbots are gaining popularity across industries, including academia. However, empirical research on academicians’ adoption behavior is limited. This study proposes an integrated model incorporating TTF factors and social network characteristics like density, homophily, and connectedness to understand academics’ continuance intentions. Methodology: A qualitative study involving 31 interviews of academics from India examined attitudes and the potential role of social network characteristics like density, homophily, and connectedness in adoption. Results showed positive sentiment towards chatbots and themes on how peer groups accelerate diffusion. In the second phase, a survey of 448 faculty members from prominent Indian universities was conducted to test the proposed research model. Contribution: The study proposes and validates an integrated model of TTF and social network factors that influence academics’ continued usage intentions toward AI chatbots. It highlights the nuanced role of peer networks in shaping adoption. Findings: Task and technology characteristics positively affected academics’ intentions to continue AI chatbot usage. Among network factors, density showed the strongest effect on TTF and perceived usefulness, while homophily and connectedness had partial effects. The study provides insights into designing appropriate AI tools for the academic context. Recommendations for Practitioners: AI chatbot designers should focus on aligning features to academics’ task needs and preferences. Compatibility with academic work culture is critical. Given peer network influences, training and demonstrations to user groups can enhance adoption. Platforms should have capabilities for collaborative use. Targeted messaging customized to disciplines can resonate better with academic subgroups. Multidisciplinary influencers should be engaged. Concerns like plagiarism risks, privacy, and job impacts should be transparently addressed. Recommendation for Researchers: More studies are needed across academic subfields to understand nuanced requirements and barriers. Further studies are recommended to investigate differences across disciplines and demographics, relative effects of specific network factors like size, proximity, and frequency of interaction, the role of academic leadership and institutional policies in enabling chatbot adoption, and how AI training biases impact usefulness perceptions and ethical issues. Impact on Society: Increased productivity in academia through the appropriate and ethical use of AI can enhance quality, access, and equity in education. AI can assist in mundane tasks, freeing academics’ time for higher-order objectives like critical thinking development. Responsible AI design and policies considering socio-cultural aspects will benefit sustainable growth. With careful implementation, it can make positive impacts on student engagement, learning support, and research efficiency. Future Research: Conduct longitudinal studies to examine the long-term impacts of AI chatbot usage in academia. Track usage behaviors over time as familiarity develops. Investigate differences across academic disciplines and roles. Requirements may vary for humanities versus STEM faculty or undergraduate versus graduate students. Assess user trust in AI and how it evolves with repeated usage, and examine trust-building strategies. Develop frameworks to assess pedagogical effectiveness and ethical risks of conversational agents in academic contexts.

This research introduces a hybrid honeypot architecture to bolster security within software-defined networks (SDNs). By combining low-interaction and high-interaction honeypots, the proposed solution effectively identifies and mitigates cyber threats, including port scanning and man-in-the-middle attacks. The architecture is structured into multiple modules that focus on detecting open ports using Vilhala honeypots and simulating targeted and random attack scenarios. This hybrid approach enables comprehensive monitoring and detailed packet-level analysis, providing enhanced protection against advanced online threats. The study also conducts a comparative analysis of different attack detection methods using tools like KFSensor and networking shell commands. The results highlight the hybrid honeypot system's efficacy in filtering malicious traffic and detecting security breaches, making it a robust solution for safeguarding SDNs.

This study aims to examine the intellectual capital and its effect on the financial performance of Ethiopian private commercial banks using the pulic model. Quantitative panel data from audited annual reports of Ethiopian private commercial banks from 2011 to 2019 are collected. The robust fixed effect regression model has been adopted to investigate the effect of IC and the financial performance measures of the banks. The study results show a positive relationship between the value added intellectual coefficient (VAIC) and the financial performance of private commercial banks in Ethiopia. The study also revealed that the components of VAIC (i.e., human capital efficiency, capital employed efficiency, and structural capital efficiency) have a positive and significant effect on the financial performance of banks measured by return on asset and return on equity over the study periods. Practically, the results of the study could be useful for shareholders to consider IC as a strategic resource and hence emphasise these intangibles, and to the bank managers to benchmark themselves against the best competitors based on the level of efficiency rankings.

The purpose of this study is to explore the effect of electronic service quality subdimensions upon the behavioural and praising intentions of users engaged in internet banking. Using the survey method, 203 responses were collected from users of online banking in Turkey. A partial least square structural equation model was constructed to test both the reliability and validity of the measurement, as well as the structural model. The results indicated that emotional benefits, ease of use, and control subdimensions, which are influenced through graphical quality and layout clarity, have a significant and positive impact upon the behavioural and praising intentions of users of online banking. The study did not find support for the direct effect of layout clarity upon behavioural and praising intentions.

The present study attempts to find out the determinants of FinTech adoption for financial inclusion by a microfinance institution in India. The factors such as efficiency, consistency, convenience, reliability are taken as predictors of organisational attitude. Similarly, organisational attitude, ease of use, and perceived benefits are considered as antecedents of organisational adoption intention of FinTech in microfinance institutions of India. The purposive sampling technique was used to get a filled survey instrument by target samples. The results indicate that convenience and consistency in the use of FinTech applications build a favourable attitude to adopt it. Furthermore, perceived benefits are the most important antecedents of the adoption intention of FinTech in the microfinance institution in India. Additionally, the reliability of the application has a positive but insignificant impact on organisational attitude to adopt FinTech. The implications of the present study are discussed.

In several manufacturing firms, inventory constitutes most of the current assets, and this underscores the importance of inventory management as a fundamental issue for the majority of the firms irrespective of their sizes. Therefore, the purpose of this research is to assess the factors that influence the effectiveness of inventory management of Malaysian SMEs in the manufacturing sector. The study employs PLS-SEM technique to test the hypotheses. The main findings show that documentation and records, inventory control system and qualified personnel have positive effects on effective inventory management of Malaysian SMEs in the manufacturing sector. The study also reveals that effective inventory management has a mediating effect on the relationship between documentation and records, inventory control system, qualified personnel and organisational performance. Therefore, the study recommends that Malaysian SMEs in the manufacturing sector should improve their approaches to embracing effective inventory management practices in order to enhance organisational performance.

Aiming at the problems of long evaluation time and poor evaluation accuracy of existing evaluation methods, an improved decision tree-based evaluation method for the effectiveness of college online course teaching reform is proposed. Firstly, the teaching mode of college online course is analysed, and an evaluation system is constructed to ensure the applicability of the evaluation method. Secondly, AHP entropy weight method is used to calculate the weights of evaluation indicators to ensure the accuracy and authority of evaluation results. Finally, the evaluation model based on decision tree algorithm is constructed and improved by fuzzy neural network to further optimise the evaluation results. The parameters of fuzzy neural network are adjusted and gradient descent method is used to optimise the evaluation results, so as to effectively evaluate the effect of college online course teaching reform. Through experiments, the evaluation time of the method is less than 5 ms, and the evaluation accuracy is more than 92.5%, which shows that the method is efficient and accurate, and provides an effective evaluation means for the teaching reform of online courses in colleges and universities.

In order to improve the mental health level of college students, a data mining based mental health education strategy for college students is proposed. Firstly, analyse the characteristics of data mining and its potential value in mental health education. Secondly, after denoising the mental health data of college students using wavelet transform, data mining methods are used to identify the psychological crisis status of college students. Finally, based on the psychological crisis status of college students, measures for mental health education are proposed from the following aspects: building a psychological counselling platform, launching psychological health promotion activities, establishing a psychological support network, strengthening academic guidance and stress management. The example analysis results show that after the application of the strategy in this article, the psychological health scores of college students have been effectively improved, with an average score of 93.5 points.

In order to improve the evaluation effect of current university teaching reform, a new method for evaluating the quality of university course teaching reform is proposed based on data mining algorithms. Firstly, the optimal data clustering criterion was used to select evaluation indicators and a quality evaluation system for university curriculum teaching reform was established. Next, a reform quality evaluation model is constructed using BP neural network, and the training process is improved through genetic algorithm to obtain the model weight and threshold of the optimal solution. Finally, the calculated parameters are substituted into the model to achieve accurate evaluation of the quality of university curriculum teaching reform. Selecting evaluation accuracy and evaluation efficiency as evaluation indicators, the practicality of the proposed method was verified through experiments. The experimental results showed that the proposed method can mine teaching reform data and evaluate the quality of teaching reform. Its evaluation accuracy is higher than 96.3%, and the evaluation time is less than 10ms, which is much better than the comparison method, fully demonstrating the practicality of the method.

Research on the quality evaluation of teaching reforms plays an important role in promoting improvements in teaching quality. Therefore, an evaluation method of teaching reform quality in colleges and universities based on big data analysis is proposed. A multivariate logistic model is used to select the evaluation indicators for the quality evaluation of teaching reforms in universities. And clustering and cleaning of the evaluation indicator data are performed through big data analysis. The evaluation indicator data is used as input vectors, and the results of the teaching reform quality evaluation are used as output vectors. A support vector machine model based on the whale algorithm is built to obtain the relevant evaluation results. Experimental results show that the proposed method achieves a minimum recall rate of 98.7% for evaluation indicator data, the minimum data processing time of 96.3 ms, the accuracy rate consistently above 97.1%.

In order to improve the comprehensiveness of evaluation results and reduce errors, a teaching reform quality evaluation method based on fuzzy comprehensive evaluation is proposed. Firstly, on the premise of meeting the principles of indicator selection, factor analysis is used to construct an evaluation indicator system. Then, calculate the weights of various evaluation indicators through fuzzy entropy, establish a fuzzy evaluation matrix, and calculate the weight vector of evaluation indicators. Finally, the fuzzy cognitive mapping method is introduced to improve the fuzzy comprehensive evaluation method, obtaining the final weight of the evaluation indicators. The weight is multiplied by the fuzzy evaluation matrix to obtain the comprehensive evaluation result. The experimental results show that the maximum relative error of the proposed method's evaluation results is about 2.0, the average comprehensive evaluation result is 92.3, and the determination coefficient is closer to 1, verifying the application effect of this method.

The research goal is to solve the problems of low accuracy and long time existing in traditional teaching reform performance evaluation methods, a performance evaluation method of teaching reform based on hierarchical multi-task deep learning is proposed. Under the principle of constructing the evaluation index system, the evaluation indicator system should be constructed. The weight of the evaluation index is calculated through the analytic hierarchy process, and the calculation result of the evaluation weight is taken as the model input sample. A hierarchical multi-task deep learning model for teaching reform performance evaluation is built, and the final teaching reform performance score is obtained. Through relevant experiments, it is proved that compared with the experimental comparison method, this method has the advantages of high evaluation accuracy and short time, and can be further applied in relevant fields.