Development and evaluation of an engagement/burnout structural model within the mining and construction equipment supplier industry by Pienaar, Deidre

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When UTAUT2 meets design thinking mindset: Exploring e-learning champions? Adoption of blended learning at EMU by Issufo, Vali

“…This research contributes to a local understanding of the factors motivating lecturers' uptake of blended learning. Thus, to boost blended learning uptake, institutions should not only focus on Facilitating Conditions such as technological infrastructure and staff training, but also create a less pressured and more empathetic environment where lectures feel at ease with what they do not know, are presented with a modest but steady adoption process, and where educational technologies contribute to the improvement of their work-life balance. …”
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Cooperative multi-agent reinforcement learning in sparse-reward, partially observable 3d environments with curriculum-transfer learning by Denkema, De Wet

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To e-learn or not to e-learn: an investigation into the efficacy, efficiency and effectiveness of converting compulsory staff training from classroom to computer by Rogerson , Christine Fiona Jane

“…The in depth literature review of e-learning implementations, success factors and barriers to adoption is followed by the discussion of the research philosophy and objectives. …”
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Deep learning for tabular data : an exploratory study by Marais, Jan Andre

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Small-scale distributed machine learning in R by Taylor, Brenden

“…The implication that this research aims to explore, is that students will be able to leverage the many computers often available in computer labs to train more complex machine learning models in less time than they would otherwise be able to when using the built-in parallel packages that are already common in R. …”
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Grade 9 learners' opportunity to learn algebra

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Applying the Seven Principles of Learning to Development Communication by Abd El Ghaffar, Lina

“…The suggested learning paradigm builds its conceptual model around the development communication campaign audience’s internal and external factors that directly influence their decision making. …”
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Influencer Wisdom As A Conceptual Model To Understand Influencer Strategies, Tactics, And Success by Asaad, Mariam Ashraf

“…Findings demonstrate how wisdom-based practices create deeper audience connections, more resilient careers, and positive social impact. …”
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Optimizing learning & teaching on paediatric ward rounds by Mantzor, Savarra

“…Bandura's Social Cognitive Theory asserts that an individual's perceptions of his/her self-efficacy influence not only their ability to learn knowledge and skill, but more importantly, influences their ability to act utilizing that knowledge or skill. …”
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Knowledge management and the learning organisation in the new economy by De Wet, Ben

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Based on the Dual Pathway of Interaction-Mediated NF-κB in Cell Apoptosis and Immune Inflammation to Study the Effect of Danzhi Xiaoyao Powder on the Learning and Cognitive Ability of AD Model Rats

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Machine learning model based analysis of land use land cover change and assessing its potential impact on surface runoff in meki watershed, rift valley lakes basin, Ethiopia

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Deep adaptive anomaly detection using an active learning framework by Sekyi, Emmanuel

“…Ahunt can therefore overcome a poor choice of features that happen to be suboptimal for detecting anomalies in the data, learning more appropriate features. We also explore the role of the loss function and Active Learning query strategy, showing these are important, especially when there is a significant variation in the anomalies.…”
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Trends, problems, and solutions in causality and reinforcement learning by Grimbly, St John

“…Although relevant in both model-based and model-free scenarios, focus is placed on model-based modalities where one can view the various models as being causal models. …”
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Social entrepreneurs’ conceptions of incubator-based learning

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Evaluating transformers as memory systems in reinforcement learning by Makkink, Thomas

“…Early research into transformers as memory mechanisms for reinforcement learning indicated that the canonical model is not suitable, and that additional gated recurrent units and architectural modifications are necessary to stabilize these models. …”
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Predicting mergers and acquisitions using machine learning by Beckenstrater, Gordon

“…The findings are that all the advanced algorithms surpassed the performance of logistic regression in M&A prediction, signalling a shift from traditional statistical methods to advanced machine learning techniques. LightGBM and the Ensemble model displayed the best performance in M&A prediction. …”
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Reinforcement learning for the control of traffic flow on highways by Schmidt-Dumont, Thorsten

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Learning from failure in the context of business rescue

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