Intensive Modes of Study and the Need to Focus on the Process of Learning in Higher Education
Abstract
In the context of a constantly evolving international higher education sector, this commentary emphasises the need for consilience between basic research on learning processes and observations from intensive modes of study. Following a discussion of conflicting evidence on optimal learning time frames, we advocate for seeking alignment between classroom practices with underlying learning mechanisms. We argue for a unified understanding of effective learning beyond notions of the credit point hour or volume of learning, focusing on processes rather than mere inputs and outputs. A collaborative approach between researchers, educators, and policymakers aiming for consilience has the potential to provide practical insights and strategies to enhance student learning and success. Understanding the mechanisms beneath the impact of intensive modes of study, as outlined in this special issue, has the potential to advance the conversation about quality higher education for the 21st century.
... Of course, good pedagogical design of assessment, appropriate supervision, reflective activities, and strong feedback practices matter for all work-based WIL experiences yet more concerted efforts are needed to upskill preceptors and students with disabilities in how to seek feedback and develop WIL literacies. This re-centring on the process of learning, rather than learning outcomes, is critical amid increased use of GenAI in higher education (Lodge & Ashford-Rowe, 2024) and must include attending to the varying supports needed by diverse student groups. ...
The global push towards widening participation for equity cohorts,
including students with disabilities, is promising, but it is yet to
translate into improved employment experiences. In this
commentary, we highlight what higher education institutions must
now do to drive meaningful change and better support students
with disabilities’ workforce transitions. In doing so, we advocate for
a much-needed change towards inclusive work-integrated learning
practices that enable students with disabilities to leverage these
opportunities to trial career pathways, build networks, and develop
their future career goals. Necessary in this is the adoption of co-
designed work-integrated learning, that brings together students
with disabilities, industry and community, and academics to ensure
non-ableist inclusive practices and a culture which understands the
strength in diversity.
Generative artificial intelligence (AI) has taken the world by storm. In this editorial, we outline some of the key areas of tertiary education impacted by large language models and associated applications that will require re-thinking and research to address in the short to medium term. Given how rapidly generative AI developments are currently occurring, this editorial is speculative. Although there is a long history of research on AI in education, the current situation is both unprecedented and seemingly not something that the AI in education community fully predicted. We also outline the editorial position of AJET in regards to generative AI to assist authors using tools such as ChatGPT as any part of the research or writing process. This is a rapidly evolving space. We have attempted to provide some clarity in this editorial while acknowledging that we may need to revisit some or all of what we offer here in the weeks and months ahead.
In this paper, we argue that a particular set of issues mars traditional assessment practices. They may be difficult for educators to design and implement; only provide discrete snapshots of performance rather than nuanced views of learning; be unadapted to the particular knowledge, skills, and backgrounds of participants; be tailored to the culture of schooling rather than the cultures schooling is designed to prepare students to enter; and assess skills that humans routinely use computers to perform. We review extant artificial intelligence approaches that–at least partially–address these issues and critically discuss whether these approaches present additional challenges for assessment practice.
‘Pedagogy first’ has become a mantra for educators, supported by the metaphor of the ‘pedagogical horse’ driving the ‘technological cart’. Yet putting technology first or last separates it from pedagogy, making us susceptible to technological or pedagogical determinism (i.e. where technology is seen either as the driving force of change or as a set of neutral tools). In this paper, I present a model of entangled pedagogy that encapsulates the mutual shaping of technology, teaching methods, purposes, values and context. Entangled pedagogy is collective, and agency is negotiated between teachers, students and other stakeholders. Outcomes are contingent on complex relations and cannot be determined in advance. I then outline an aspirational view of how teachers, students and others can collaborate whilst embracing uncertainty, imperfection, openness and honesty, and developing pedagogical knowledge that is collective, responsive and ethical. Finally, I discuss implications for evaluation and research, arguing that we must look beyond isolated ideas of technologies or teaching methods, to the situated, entangled combinations of diverse elements involved in educational activity.
The first year in Higher Education (HE) is an international priority because of its importance to the retention of students. While initiatives to improve students’ commencing experience continue to develop one area that has received limited consideration is the first‐year curriculum. The aim of the research reported in this paper was to enhance the student experience in HE by expanding understandings of the first‐year curriculum. Focus groups and an online questionnaire were the research methods used to, explore students’ experiences of learning in a newly developed First‐Year Block Model (FYBM) curriculum, implemented at a university in Australia. Findings from the research revealed that features in the design of the FYBM framed and permeated the students’ experiences of learning. The students explained that a sense of familiarity, curriculum leadership, teaching and teachers and curriculum customisation influenced their engagement and achievements. The study highlights that HE requires staff who possess deep knowledge and expertise in the first‐year curriculum because this valuable asset can positively influence student learning and success.
An interleaved presentation of items (as opposed to a blocked presentation) has been proposed to foster inductive learning (interleaving effect). A meta-analysis of the interleaving effect (based on 59 studies with 238 effect sizes nested in 158 samples) was conducted to quantify the magnitude of the interleaving effect, to test its generalizability across different settings and learning materials, and to examine moderators that could augment the theoretical models of interleaved learning. A multilevel meta-analysis revealed a moderate overall interleaving effect (Hedges’ g = 0.42). Interleaved practice was best for studies using paintings (g = 0.67) and other visual materials. Results for studies using mathematical tasks revealed a small interleaving effect (g = 0.34), whereas results for expository texts and tastes were ambiguous with nonsignificant overall effects. An advantage of blocking compared to interleaving was found for studies based on words (g = -0.39). A multiple meta-regression analysis revealed stronger interleaving effects for learning material more similar between categories, for learning material less similar within categories, and for more complex learning material. These results are consistent with the theoretical account of interleaved learning, most notably with the sequential theory of attention (attentional bias framework). We conclude that interleaving can effectively foster inductive learning but that the setting and the type of learning material must be considered. The interleaved learning, however, should be used with caution in certain conditions, especially for expository texts and words.
Credit hours traditionally quantify expected instructional time per week in a course, informing student course selection decisions and contributing to degree requirement satisfaction. In this study, we investigate determinants of course load beyond this metric, including from course assignment structure and LMS interactions. Collecting 596 course load ratings on time load, mental effort, and psychological stress, we investigate to what extent course design decisions gleaned from LMS data explain students’ perception of course load. We find that credit hours alone explain little variance compared to LMS features, specifically number of assignments and course drop ratios late in the semester. Student-level features (e.g., satisfied prerequisites, course GPA) exhibited stronger associations with course load than number of credit hours; however, they added only little explained variance when combined with LMS features. We analyze students’ perceived importance and manageability of course load and argue in favor of a more holistic construct of course load.
This chapter provides a critical review of recently published empirical papers on highly intensive teaching in higher education. Highly intensive teaching refers to subjects taught face-to-face in four weeks or less. Building upon and extending an influential review of intensive mode delivery (IMD) in higher education by Davies in 2006, this literature review confirms the observation made by several scholars investigating IMD that despite the increasing popularity of this form of delivery, rigorous and methodologically robust research into the benefits and challenges of this form of pedagogy is still in its infancy. By applying cognitive learning theory, this chapter discusses the circumstances under which intensive mode teaching is likely to be most effective and outlines potential avenues for further research.
High-quality teaching is central to the higher education sector. Its pursuit has become heightened with increasing competition across institutions and opportunities to study globally through various modes. This systematic meta-review provides a synthesis of evidence relating to the methods used to assess and enhance the quality of teaching practice within higher education. Key words, synonyms and subject headings were used to search six electronic databases between January 2009 and August 2019. Titles and abstracts of publications were screened and full text articles assessed against the eligibility criteria. Findings were extracted and integrated in a narrative synthesis. Thirteen review articles, revealed that the use of teaching quality: student feedback data, self-assessment tools, peer review of teaching (formative and summative) and the use of teaching portfolios. We report evidence related to the effectiveness of each of these approaches and that a multi-modal approach may be most effective but requires consideration of resourcing.
The interdisciplinary field of the learning sciences encompasses educational psychology, cognitive science, computer science, and anthropology, among other disciplines. The Cambridge Handbook of the Learning Sciences, first published in 2006, is the definitive introduction to this innovative approach to teaching, learning, and educational technology. In this dramatically revised second edition, leading scholars incorporate the latest research to provide practical advice on a wide range of issues. The authors address the best ways to write textbooks, design educational software, prepare effective teachers, organize classrooms, and use the Internet to enhance student learning. They illustrate the importance of creating productive learning environments both inside and outside school, including after school clubs, libraries, and museums. Accessible and engaging, the Handbook has proven to be an essential resource for graduate students, researchers, teachers, administrators, consultants, software designers, and policy makers on a global scale.