Volume 5 (2026-2027)

As machine learning (ML) models are increasingly used to support decision making in higher education, there is a growing need to move beyond accurate prediction toward explanations that enable meaningful intervention. This paper examines counterfactual explanations (CFEs) as prescriptive complements to risk prediction in educational data analytics. While predictive models can flag students at risk, their practical value is limited without actionable guidance. CFEs address this need by proposing small, feasible changes that may shift a prediction from at-risk to not at-risk. Three approaches are compared on the Student Insomnia and Educational Outcomes (SIEO) dataset using a LightGBM classifier as the predictive backbone: DiCE (genetic search), the method of Wachter et al. (optimisation with proximity penalties), and a FACE-lite approximation that follows manifold-constrained paths via nearest-neighbour graphs. Demographic variables (eg gender, year of study) are treated as immutable; behavioural and psychological features (eg sleep duration, fatigue, stress) are allowed to vary. Counterfactual quality is assessed by validity, proximity, sparsity, and plausibility. Results indicate that improving sleep, reducing fatigue, and lowering stress frequently appear as pathways for altering model outputs. The comparison suggests distinct trade-offs: DiCE tends to increase diversity with occasional plausibility concerns; Wachter emphasises minimal changes with more repetitive adjustments; FACE-lite balances plausibility with structural constraints. Taken together, these findings point to CFEs as a practical complement to predictive analytics, offering individualised recommendations that can inform advising and student support. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: counterfactual explanations; prescriptive analytics; educational data mining; LightGBM; student success; model interpretability

This conceptual synthesis examines why artificial intelligence (AI) text detection cannot be treated as equivalent to plagiarism detection in cases of academic misconduct. Plagiarism detection tools operate forensically: they identify specific passages, match them to verifiable sources, and produce evidence that both instructors and students can examine and rebut. AI detectors operate statistically: they estimate the probability that a text resembles AI-generated writing, without identifying a source, act, or comparator. Drawing on independent evaluations showing no tool exceeds 80 per cent accuracy,1 false-positive rates above 61 per cent for non-native English writers in a Test of English as a Foreign Language (TOEFL)-essay testing condition,2 and journalistic survey evidence reporting disproportionate false-accusation experiences among Black students,3 the paper applies three lenses. First, evidentiary: AI scores are not falsifiable and suffer base-rate problems that make predictive value unknowable in real classrooms. Secondly, procedural: under Goss v. Lopez (1975) and Mathews v. Eldridge (1976), students are entitled to notice and a meaningful opportunity to respond, a safeguard undermined when the evidence is an opaque probability. Thirdly, fairness: applying Rawlsian justice, rational agents behind a veil of ignorance would reject a system whose errors fall most heavily on non-native speakers and on groups that survey evidence suggests may face disproportionate risk of accusation. Recent reporting on one federal preliminary ruling suggests discipline is more defensible when institutions rely on corroborating evidence, not scores alone. The paper concludes that detection outputs should never serve as standalone proof and recommends process-based assessment, bias audits, and transparent policies. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: AI detection; academic integrity; plagiarism detection; procedural justice; bias; higher education; evidence

This paper examines the development of systems thinking (ST) skills among college students and graduates, extending prior research that highlights the importance of ST in addressing complex real-world challenges. While earlier studies identified positive perceptions and applications of ST skills, less is known about how these skills evolve as individuals transition from academic to professional contexts. Using a comparative qualitative approach, this study analyses open-ended survey responses from 403 participants. The analysis explores two dimensions of ST: how individuals apply ST in practice (‘what they do’) and the cognitive patterns that underpin these processes (‘how they think’), with particular attention to differences in scope, complexity, and integration across groups. Findings reveal a clear developmental progression in ST. Students tend to apply these skills in bounded, task-focused contexts, emphasising problem identification, root-cause analysis, and localised efficiency improvements. In contrast, graduates demonstrate more advanced capabilities, including system-wide perspectives, dynamic collaboration, and the ability to manage complex interdependencies. This shift reflects a transition from individual, short-term problem solving towards more integrated, adaptive, and strategic decision making with a longer-term, system-wide perspective. These findings suggest that ST develops through experiential learning and real-world exposure. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: business education; career readiness; higher education; problem solving; systems thinking; workforce preparedness

Online medical laboratory science (MLS) degree advancement programmes have become a vital pathway for working medical laboratory technicians (MLTs) seeking bachelor’s-level education, professional advancement, and eligibility for expanded career opportunities. Successful online programme design, however, requires more than simply transferring didactic content into a virtual format. Working adult learners often evaluate programmes based on flexibility, responsiveness, academic quality, affordability, certification preparation, and the credibility of online assessment practices. This descriptive case study examines student expectations in online MLT-to-MLS education, using the University of Arkansas for Medical Sciences (UAMS) online MLT-to-MLS programme as an example. The paper identifies practical design considerations for institutions developing or revising online MLT-MLS programmes, including asynchronous delivery, distributed faculty support, certification-focused curriculum alignment, transparent cost structures, and secure assessment strategies. Particular attention is given to assessment integrity, including proctoring, exam design, identity verification, and the alignment between assessment methods and professional competency expectations. In summary, this paper provides educators and administrators with a practical framework for designing online MLS programmes that are flexible, academically rigorous, studentcentred, and responsive to current workforce needs. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: medical laboratory science; distance education; MLT-to-MLS; asynchronous learning; flexibility; faculty support; career advancement; affordability; assessment integrity

Negotiation is a critical skill in business, engineering, and everyday life, yet teaching negotiation strategies can be challenging due to the complexity and dynamic nature of interactions. Modelling and simulation, particularly agent-based modelling (ABM), offers a powerful tool to support experiential and online learning in this context. This paper presents NegSim, an ABM developed using NetLogo, designed to help students explore, practise, and understand negotiation strategies in a simulated, interactive environment. The simulation allows learners to experiment with agent behaviours, visualise key negotiation concepts such as Best Alternative to a Negotiated Agreement (BATNA) and Zone of Possible Agreement (ZOPA), and observe the outcomes of distributive negotiation scenarios. The paper details the methodology for designing the simulation, integrating it into classroom instruction, and leveraging it as a pedagogical tool to enhance critical thinking, strategy development, and decision-making skills. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: learning; simulation; negotiation; strategy; classroom

Adult learners often pursue higher education while managing employment, caregiving duties, financial pressures, and other competing demands. Although extensive research has identified factors related to learner engagement, persistence, and success in online settings, faculty frequently receive limited guidance on how to apply these theoretical principles consistently in their teaching. This conceptual framework paper aims to bridge that theory–practice gap by creating a practitioner-focused implementation framework for adult online learning. The paper introduces the See the whole student, Teach with clarity, Engage with humility, Provide timely support, and Sustain hope (STEPS) framework as a conceptual and practical model designed to implement established principles of effective online teaching. STEPS was developed through an integrative conceptual synthesis and design-based approach rather than as a systematic literature review or an empirical validation study. Drawing from the Community of Inquiry, andragogy, transactional distance theory, pedagogies of care, and adult learner persistence scholarship, this paper explains the theoretical bases of each dimension, highlights observable teaching practices linked to each component, and clarifies the framework’s intended purpose. The value of STEPS lies not in proposing a new learning theory but in translating existing research into a clear, actionable structure for faculty, instructional designers, faculty developers, and scholar-practitioners supporting adult online learners. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.
Keywords: adult learning; care; support; engagement; presence