This study explores the impact of online assessments on students’ academic performance and learning outcomes at the University of Technology in South Africa. The research problem addresses the effectiveness and challenges of digital assessment platforms in higher education (HE), particularly their influence on student engagement, feedback quality, and academic integrity. A qualitative case study approach was employed, involving semi-structured interviews with ten undergraduate and postgraduate students from diverse academic backgrounds. The findings reveal that while online assessments provide flexibility and immediate feedback, they also pose challenges related to technical issues, feedback delays, and concerns about long-term knowledge retention. The study highlights the necessity of aligning assessment strategies with constructivist learning principles to enhance critical thinking and student-centered learning. Implications for theory include strengthening the application of constructivist learning in digital environments, while practical recommendations focus on improving assessment design, institutional support, and feedback mechanisms. Policy adjustments should consider inclusive and equitable access to online assessments. Future research should further investigate the long-term impact of digital assessments on professional readiness. This study contributes to ongoing discussions on online education by offering a nuanced understanding of digital assessment challenges and opportunities in higher education.

Photovoltaic systems have shown significant attention in energy systems due to the recent machine learning approach to addressing photovoltaic technical failures and energy crises. A precise power production analysis is utilized for failure identification and detection. Therefore, detecting faults in photovoltaic systems produces a considerable challenge, as it needs to determine the fault type and location rapidly and economically while ensuring continuous system operation. Thus, applying an effective fault detection system becomes necessary to moderate damages caused by faulty photovoltaic devices and protect the system against possible losses. The contribution of this study is in two folds: firstly, the paper presents several categories of photovoltaic systems faults in literature, including line-to-line, degradation, partial shading effect, open/close circuits and bypass diode faults and explores fault discovery approaches with specific importance on detecting intricate faults earlier unexplored to address this issue; secondly, VOSviewer software is presented to assess and review the utilization of machine learning within the solar photovoltaic system sector. To achieve the aims, 2258 articles retrieved from Scopus, Google Scholar, and ScienceDirect were examined across different machine learning and energy-related keywords from 1990 to the most recent research papers on 14 January 2025. The results emphasise the efficiency of the established methods in attaining fault detection with a high accuracy of over 98%. It is also observed that considering their effortlessness and performance accuracy, artificial neural networks are the most promising technique in finding a central photovoltaic system fault detection. In this regard, an extensive application of machine learning to solar photovoltaic systems could thus clinch a quicker route through sustainable energy production.

The Agriculture Trading Platform (ATP) represents a significant innovation in the realm of agricultural trade in Malaysia. This web-based platform is designed to address the prevalent inefficiencies and lack of transparency in the current agricultural trading environment. By centralizing real-time data on agricultural production, consumption, and pricing, ATP provides a comprehensive dashboard that facilitates data-driven decision-making for all stakeholders in the agricultural supply chain. The platform employs advanced deep learning algorithms, including Long Short-Term Memory (LSTM) networks and Convolutional Neural Networks (CNN), to forecast market trends and consumption patterns. These predictive capabilities enable producers to optimize their market strategies, negotiate better prices, and access broader markets, thereby enhancing the overall efficiency and transparency of agricultural trading in Malaysia. The ATP’s user-friendly interface and robust analytical tools have the potential to revolutionize the agricultural sector by empowering farmers, reducing reliance on intermediaries, and fostering a more equitable trading environment.

The global agreement on environmentally friendly policies puts pressure on businesses to implement good practices to increase legitimacy in a competitive environment. This research aims to examine business dynamic capabilities and value creation processes through the concept of green dynamic marketing capabilities. This concept addresses the ability of businesses to absorb, manage information and accumulate new knowledge that fuels innovative endeavors. The dynamic capability view and customer value theory are integrated to theoretically explain the value creation process of market-orientated innovative products. A total of 58 global companies in Clean200 were sampled. A quantitative approach was conducted to measure the effect of organizational learning (environment management team, environment management training, environment supply chain management) on green innovation (environmental innovation score, eco design product). The results showed that the contribution of Model-1 (0.473 or 47.3%) explained the effect of organizational learning on environmental innovation score, respectively on the variables of environment management team (2.859/0.005), environment management training (−2.971/0.003), and environment supply chain management (7.786/0.000). The contribution of Model-2 (0.448/44.8%) explains the effect of organizational learning on eco-design product, respectively on the variables of environment management team (4.280/0.000), environment management training (−6.401/0.000), and environment supply chain management (7.910/0.000). Model-3 tested the structural association variables in organizational learning and green innovation. A significant influence can be seen with a probability value smaller than 0.05. This research shows that the concept of green dynamic marketing capabilities can be used to explain the ability of businesses in response to the pressure of green global norms through the development of organizational learning towards creation of green innovation product that has impact on market performance. The implication of this research is the creation of new mindset in which green global norms challenge becomes an opportunity for businesses to improve competitiveness.

Recovery and resilience plan (RRP) approved by the European Commission fosters the development of lifelong learning programs to upgrade employees’ skills and knowledge for digital and green transitions. Within higher education, the field of information and communication technology (ICT) is also a priority area, so we compared the demographic variables of students enrolled in formal first-cycle higher education programs in ICT with those enrolled in lifelong ICT programs within the framework of the Advanced Computer Skills project funded by the RRP in Slovenia. The results show that formal first-cycle higher education in the field of ICT remains strongly male-dominated, whereas, among participants in lifelong learning, the percentage of females stands out. Bachelor programs in ICT are primarily enrolled by young people aged up to 24 years, while shorter university-based lifelong learning programs attract mostly older participants with higher completed formal education and from a broader range of prior educational backgrounds. Finally, when all three variables (gender, age and level of prior formal education) are considered, participants in lifelong learning are much more similar to part-time students than full-time bachelor ICT students, although the percentage of men in formal education is still predominant even in part-time studies. The research findings highlight the need for further efforts to offer lifelong learning in ICT to enable individuals to improve their employment prospects, progress in the workplace or even change their field of work.