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The rapid adoption of AI tools such as ChatGPT has significantly transformed academic practices, offering considerable benefits for both students and faculty in computing disciplines. These tools have been shown to enhance learning efficiency, academic self-efficacy, and confidence. However, their increasing use also raises pressing concerns regarding the preservation of academic integrity -- an essential pillar of the educational process. This paper explores the implications of widespread AI tool usage within computing colleges, with a particular focus on how to align their use with the principles of academic honesty. We begin by classifying common assessment techniques employed in computing education and examine how each may be impacted by AI-assisted tools. Building on this foundation, we propose a set of general guidelines applicable across various assessment formats to help instructors responsibly integrate AI tools into their pedagogy. Furthermore, we provide targeted, assessment-specific recommendations designed to uphold educational objectives while mitigating risks of academic misconduct. These guidelines serve as a practical framework for instructors aiming to balance the

The main aim of this study was to assess and evaluate user satisfaction with library resources and services among library users associated with Solapur University. The current research shows the level of users satisfaction with different library resources and services offered by college libraries. The research found that a vast number of respondents were pleased with library facilities and services. The research is designed to achieve users satisfaction in the library to investigate the level of satisfaction towards library resources and services with regards to 26 colleges of Solapur University based in Maharashtra. Information in the form of data has been collected from colleges and on the basis of users results; analysis needs to analyze users satisfaction.

Successful careers are built on Skills (what you know), Occupational Identity (what you believe you can be) and Social Capital (who you know). Higher-ed spends significant resources in addressing the first, sometimes to the exclusion of the other two - which are difficult and expensive to teach and administer. This research specifically explores how near-peer mentoring programs, rather than a stand-alone opt-in guidance, can be integrated into the instruction/pedagogy by faculty at California community colleges. The research was conducted at 5 California community colleges (Reedley, Porterville, Coalinga, Solano and Glendale). A mixed-methods approach was used to gather social cognitive measures of student self-efficacy, occupational identity and social capital access. Measures were collected using survey instruments at the beginning of the mentoring program, and at its culmination. One of the most consistent measures observed across all the pilots was the increase in student self-efficacy of skills and competencies (3% - 7%) across colleges, geographies, and course formats after the mentoring program. Additionally, the research offers insights in implementing peer and near-peer me

Automated grading systems, or auto-graders, have become ubiquitous in programming education, and the way they generate feedback has become increasingly automated as well. However, there is insufficient evidence regarding auto-grader feedback's effectiveness in improving student learning outcomes, in a way that differentiates students who utilized the feedback and students who did not. In this study, we fill this critical gap. Specifically, we analyze students' interactions with auto-graders in an introductory Python programming course, offered at five community colleges in the United States. Our results show that students checking the feedback more frequently tend to get higher scores from their programming assignments overall. Our results also show that a submission that follows a student checking the feedback tends to receive a higher score than a submission that follows a student ignoring the feedback. Our results provide evidence on auto-grader feedback's effectiveness, encourage their increased utilization, and call for future work to continue their evaluation in this age of automation

Personalized adaptive learning (PAL) stands out by closely monitoring individual students' progress and tailoring their learning paths to their unique knowledge and needs. A crucial technique for effective PAL implementation is knowledge tracing, which models students' evolving knowledge to predict their future performance. Recent advancements in deep learning have significantly enhanced knowledge tracing through Deep Knowledge Tracing (DKT). However, there is limited research on DKT for Science, Technology, Engineering, and Math (STEM) education at Historically Black Colleges and Universities (HBCUs). This study builds a comprehensive dataset to investigate DKT for implementing PAL in STEM education at HBCUs, utilizing multiple state-of-the-art (SOTA) DKT models to examine knowledge tracing performance. The dataset includes 352,148 learning records for 17,181 undergraduate students across eight colleges at Prairie View A&M University (PVAMU). The SOTA DKT models employed include DKT, DKT+, DKVMN, SAKT, and KQN. Experimental results demonstrate the effectiveness of DKT models in accurately predicting students' academic outcomes. Specifically, the SAKT and KQN models outperform

The study investigated the use of electronic resources/information by library users in selected colleges of Solapur University. Specifically, to investigate the awareness and level of use of electronic resources; perceived reliance, benefits and impact of use of electronic resources on the research activities. The research design for the study was a survey. Questionnaire schedule was used to collect data from 1022 library users from selected colleges of Solapur University. The result revealed that preponderance of users from aided 33.51% Self financing 26.10% and Education colleges 43.24 % preferred to visit the Library once in three days. While analyzing the entire college libraries regarding the frequency of visit, users gave first preference to once in three days i.e. 27.2%. College wise analysis reveals that mainstream of users from Aided Colleges 38%, Self financing Colleges 28.3%, Engineering Colleges 43%, Education colleges 53.2% and Pharmacy Colleges 23.4% are spending their time 1-2 hrs in libraries and 40.8%visit college libraries to issue and return books and in the device usage (33.9%) of users ranked mobile phone as the second device for accessing the e-resources. It i

Mental health support in colleges is vital in educating students by offering counseling services and organizing supportive events. However, evaluating its effectiveness faces challenges like data collection difficulties and lack of standardized metrics, limiting research scope. Student feedback is crucial for evaluation but often relies on qualitative analysis without systematic investigation using advanced machine learning methods. This paper uses public Student Voice Survey data to analyze student sentiments on mental health support with large language models (LLMs). We created a sentiment analysis dataset, SMILE-College, with human-machine collaboration. The investigation of both traditional machine learning methods and state-of-the-art LLMs showed the best performance of GPT-3.5 and BERT on this new dataset. The analysis highlights challenges in accurately predicting response sentiments and offers practical insights on how LLMs can enhance mental health-related research and improve college mental health services. This data-driven approach will facilitate efficient and informed mental health support evaluation, management, and decision-making.

Universities hold and process a vast amount of valuable user and research data. This makes them a prime target for cyber criminals. Additionally, universities and other educational settings, such as schools and college IT systems, have become a prime target for some of their own students -- often motivated by an opportunity to cause damage to networks and websites, and/or improve their grades. This paper provides a focused assessment of the current cyber security threat to universities, colleges, and schools (`the education sector') worldwide, providing chronological sequencing of attacks and highlighting the insider threat posed by students. Fifty-eight attacks were identified, with ransomware being the most common type of external attack, and hacking motivated by personal gain showing as the most common form of internal attack. Students, who have become a significant internal threat by either aiding or carrying out attacks are not a homogeneous group, as students may be motivated by different factors, therefore calling for targeted responses. Furthermore, the education sector is increasingly reliant on third party IT service providers meaning attacks on third parties can impact t

This study takes the development path of computer application technology specialty construction in Higher Vocational Colleges under the background of high-level higher vocational schools and specialty construction plan with Chinese characteristics (double high plan) as the main research object, and puts forward the core concept of computer application technology specialty construction and development in Higher Vocational Colleges in China through the practice of computer application technology specialty construction and development reform in recent years The main measures and construction objectives provide specific experience and solutions for deepening the reform of computer application technology specialty in higher vocational colleges.

This article attempts to comprehend the current issues and hurdles that Indian colleges affiliated with Tamil Nadu State Universities encounter when trying to subscribe to a software that detects plagiarism. The study goals are to determine whether colleges employ anti-plagiarism software, whether they ensure that their student-given assignments are free of copyright infringement, whether tutors teach about academic misconduct, and what people seem to think of anti-plagiarism software. We surveyed for this study and distributed the questionnaires among college administrators, principals, and librarians.

The long-term success of HEP lies in expanding inclusiveness beyond national labs and academic research institutions to a vast community of predominantly undergraduate institutions (PUI) and community colleges (CC). Institutions such as PUIs and CCs offer an early starting point in the pipeline that can mitigate issues of lack of diversity and underrepresented participation of different groups in HEP. However, there are many underlying systemic, structural, and cultural challenges that need to be addressed collectively. Experimental collaborations are largely populated by national labs and research-focused academic institutions (non-PUIs). The faculty at PUIs and CCs have a high teaching load that is detrimental to their research participation. In addition, there is a lack of guidance, access, and tough competition for securing research funding. The students also suffer from a lack of research infrastructure and technical equipment that can only be found at national labs and larger universities. There are existing successful efforts to enhance the HEP research experience of students and faculty members. This paper discusses ways to leverage these to provide more research opportunit

The emergence of intellectual property as an academic issue opens a big gate to a cross-disciplinary field. Different disciplines start a dialogue in the framework of the international multilateral treaties in the early 90's. As global economy demands new knowledge on intellectual property, Science grows at its own pace. However, the degree of consolidation of cross-disciplinary academic communities is not clear. In order to know how closely related are these communities, this paper proposes a mixed methodology to find invisible colleges in the production about intellectual property. The articles examined in this paper were extracted from Web of Science. The analyzed period was from 1994 to 2016, taking into account the signature of the agreement on Trade-Related Aspects of Intellectual Property Rights in the early 90's. A total amount of 1580 papers were processed through co-citation network analysis. An especial technique, which combine algorithms of community detection and defining population of articles through thresholds of shared references, was applied. In order to contrast the invisible colleges that emerged with the existence of formal institutional relations, it was made

The paper aims to present the results of a survey of academic libraries about the adoption and perceived impact of Web 2.0 technologies. A total of 26 college libraries affiliated with Solapur University participated among the members. It was found that each library was using some form of technology, such as RSS, blogs, social networking sites, wikis, and instant messaging. Analyzing the entire college web technology usages, it is observed from the results that most of the web technologies are not used by the mainstream of the users due to lack of awareness, training, etc. Accurate and appropriate training should be conducted by the colleges' Libraries according to the necessities of the users. Systematic training will inevitably help the user for the maximum utilization of e-resources of the library. The leading web technologies such as internet surfing, emails, search engines, wikis, photo sharing, etc. are used by a great number of users on a daily and weekly basis of frequency. On the other hand majority of the web technologies are never used by a great number of users.