Ben Kei Daniel

Big Data and analytics in higher education: Opportunities and challenges

Institutions of higher education are operating in an increasingly complex and competitive environment. This paper identifies contemporary challenges facing institutions of higher education worldwide and explores the potential of Big Data in addressing these challenges. The paper then outlines a number of opportunities and challenges associated with the implementation of Big Data in the context of higher education.The paper concludes by outlining future directions relating to the development and implementation of an institutional project on Big Data.

Big Data in Higher Education: The Big Picture

Globally, the landscape of higher education sector is under increasing pressure to transform its operational and governing structure; to accommodate new economic, social and cultural agendas; relevant to regional, national and international demands. As a result, universities are constantly searching for actionable insights from data, to generate strategies they can use to meet these new demands. Big Data and analytics have the potential to enable institutions to thoroughly examine their present challenges, identify ways to address them as well as predict possible future outcomes. However, because Big Data is a new phenomenon in higher education, its conceptual relevance, as well as the opportunities and limitations it might bring, is still unknown. This chapter describes the conceptual underpinning of Big Data research and presents possible opportunities as well as limitations associated with unlocking the value of Big Data in higher education.

Contestable professional academic identity of those who teach research methodology

ABSTRACT A professional academic identity is important because it supports a sense of belonging and contributes to the scholarly advancement of a discipline. However, a professional academic identity for those involved in teaching research methodology is particularly complex and diverse. This research surveyed 144 academics from 139 universities in 9 countries, who are involved in teaching research methodology, and examined the extent to which participants construct their professional academic identity around research methodology. The study also sought to examine whether participants view research methodology as a distinct discipline. Findings show that academics teaching research methods inhabit multiple identities. Some identified as expert researchers, while others associated with particular research methods, along with a clear epistemic attachment, within a particular area of scholarly inquiry. Furthermore, few participants described themselves as research methodologists, and stressed the significance of teaching research methodology as a distinct discipline. Findings also revealed that the majority of the institutions involved in the study approach research methodology as ‘a service course’ and predominantly taught by volunteer academics. This study contributes to our understanding of how research methodology courses are organized, and the broader implications of the different approaches to the scholarly advancement of research methodology as a distinct subject.

Big Data and data science: A critical review of issues for educational research

Big Data refers to large and disparate volumes of data generated by people, applications and machines. It is gaining increasing attention from a variety of domains, including education. What are the challenges of engaging with Big Data research in education? This paper identifies a wide range of critical issues that researchers need to consider when working with Big Data in education. The issues identified include diversity in the conception and meaning of Big Data in education, ontological, epistemological disparity, technical challenges, ethics and privacy, digital divide and digital dividend, lack of expertise and academic development opportunities to prepare educational researchers to leverage opportunities afforded by Big Data. The goal of this paper is to raise awareness on these issues and initiate a dialogue. The paper was inspired partly by insights drawn from the literature but mostly informed by experience researching into Big Data in education. [ABSTRACT FROM AUTHOR]

A research methodology for studying distributed communities of practice

Distributed community of practice (DCoP) is a type of a focused virtual (web) community which aims at fostering knowledge sharing and professional development. DCoP as a theoretical framework offers a way of describing and understanding how different sectors and groups can collaborate and work together under distributed circumstances on issues of shared concern. Many disciplines have used DCoP to identify ways of fostering effective collaboration and knowledge sharing with a considerable level of success. For instance, DCoP was used to describe a collaborative platform for engaging clinicians, researchers, policymakers, students and communities to work together in addressing complex clinical problems. Drawing from previous research, this article first describes the notion of DCoP as a knowledge sharing platform. It then presents a research methodology for studying DCoPs.

Empirical verification of the “TACT” framework for teaching rigour in qualitative research methodology

Purpose n n n n nThe purpose of this paper is to present a framework intended to guide students and novice researchers in learning about the necessary dimensions for assessing the rigour of qualitative research studies. The framework has four dimensions – (T)rustworthiness, (A)uditability, (C)redibility and (T)ransferability. The development of TACT is informed by various discourses of rigour in the qualitative research methods literature. Results of an empirical verification of TACT suggests that postgraduate students and faculty learning qualitative research found the framework useful for learning rigour in qualitative research methods. TACT also serves as an important theoretical tool for setting directions for further discourses on teaching and learning critical aspects of rigour in qualitative research methodology. n n n n nDesign/methodology/approach n n n n nThe formal verification of the TACT started with a development of a rating tool. The tool consisted of a total of 16 items, 4 items per each dimension. The items were ranked on five-scale Likert points (1=very important, 2=important, 3=neutral, 4=less important, 5=not important). The instrument was piloted and tested for reliability revealing an overall Cronbach’s α (α=0.86), which indicates a good level of internal consistency (George and Mallery, 2003) among the dimensions. The tool was put online and sent out to participants enroled in workshops on “assessing rigour in qualitative research studies”. n n n n nFindings n n n n nOverall, participants found TACT to be a useful framework for learning different dimensions for assessing qualitative research. They saw various benefits associated with the use of the framework including providing a better process for undertaking and reporting outcomes of qualitative research and for exploring different dimensions of rigour. Participants also indicated that using TACT facilitates reflexivity and fosters dependability of research outcomes. They stated that TACT could help researchers think about their personal relationship with a phenomenon being studied as well as the quality of data collected. Others said that TACT allows researchers to think about achieving transference and gaining confidence in the research findings. n n n n nResearch limitations/implications n n n n nTACT is best suited as a teaching toolkit in qualitative research methodology courses. It is also useful as a platform for fostering a shared language in undertaking peer-review of methodological dimensions of qualitative research studies. n n n n nPractical implications n n n n nThough a general framework for accessing rigour in qualitative research studies is highly desirable, the usefulness of TACT in rendering rigour is subject to a particular academic tradition. n n n n nSocial implications n n n n nTACT facilitates the exploration of different dimensions for assessing the outcome of qualitative research. n n n n nOriginality/value n n n n nTACT is a general framework drawn from the literature and teaching practice and empirically validated.

Postgraduate conception of research methodology: implications for learning and teaching

ABSTRACT This qualitative inquiry investigates postgraduate students’ conceptions of research methodology and how it contributes to their learning. It explores factors likely to motivate student choice of research methodology and challenges in understanding research methods. The research was carried out at research-intensive universities in New Zealand and in Malaysia with similar postgraduate programmes. Participants were enrolled in Masters and Ph.D. programmes. Findings revealed that participants share a recognition that research methodology is a significant body of knowledge in postgraduate education. However, there were noticeable differences in perspectives regarding what constitutes research methodology and whether or not it should be conceived as a discipline. To some participants, learning research methodology is less of a discipline but rather an acquisition of a set of isolated facts and skills without necessarily acquiring a deeper understanding of research. Furthermore, postgraduate students choose research methodology based on a number of factors such as familiarity with a method, methodological orientation of the primary supervisor, the domain of study, and the nature of research problems pursued. Participants reported that the key challenges they face in understanding research methodology include framing research questions, understanding the theory or literature and its role in shaping research outcomes, and difficulties in performing data analysis.

The perceptions of the meaning and value of analytics in New Zealand higher education institutions

This article presents the current perceptions on the value of analytics and their possible contribution to the higher education sector in New Zealand. Seven out of eight research-intensive public universities in New Zealand took part in the study. Participants included senior management and those who have some role associated with decision-making within higher education (Nxa0=xa082). The study found inconsistent understanding of the meaning of analytics across participants. In particular, three forms of perceptions of analytics were identified: structural; functional and structural-functional. It was evident that some participants viewed analytics in its structural elements such as statistics, metrics, trends, numbers, graph, and any relevant information/data to enhance better decision-making, whereas other participants perceived the notion of analytics in terms of functional aspect; as means to an end, a process to use the data to gain insights and taking action on complex problems, yet a third group viewed analytics from both structural-functional perspectives. These kinds of perceptions have to a larger extent influenced participants’ views on the value of analytics in shaping policy and practice. Also, literature has addressed a number of possible challenges associated with the large-scale institutional implementation of analytics. These challenges were: difficulties in extracting data from multiple databases, maintaining data quality, ethical and privacy issues, and lack of professional development opportunities. This article aims to broadly contribute to a better understanding of current perception and value of analytics in higher education, and in particular within the New Zealand context.

Integration of learning technologies into teaching within Fijian Polytechnic Institutions

In the 21st century, learning technologies have increasingly become pervasive within various forms of learning environments. Institutions of higher education are increasingly turning to these technologies to resource and support their teaching and learning environments under distributed circumstances, face-to-face or blended. Recently, the Fijian Ministry of Education systematically introduced learning technologies into Fiji’s technical colleges to support teaching and learning. However, prior to the widespread deployment of these technologies, little information was available on educators’ perception of the value of these technologies, and the extent to which this could influence adoption. The purpose of this study was to gain a better understanding of lecturers’ perceptions of the value of learning technologies and factors likely to influence their decisions to adopt and integrate these technologies into teaching as well as challenges they are likely to face. A survey was administered to fifty five self-selected lecturers involved in teaching within three Polytechnics in Fiji. Although overall findings suggested that lecturers strongly valued the contribution of learning technologies in enhancing student learning, a number of factors likely to influence the rapid adoption of these technologies were identified. These included attitude towards technology and perceived usefulness of technology in teaching, the institutional cultural environment, as well as resources available to support uptake. This research contributes to the growing significance of individual, contextual and cultural influences in the adoption of learning technologies into teaching.

The efficacy of stacked bar charts in supporting single-attribute and overall-attribute comparisons

Abstract Stacked bar charts are a visualization method for presenting multiple attributes of data, and many visualization tools support these charts. To assess the efficacy of stacked bar charts in supporting attribute-comparison tasks, we conducted a user study to compare three types of stacked bar charts: classical, inverting, and diverging. Each chart type was used to visualize six attributes of data where half of the attributes have the characteristics of ‘lower better’ whereas the other half attributes are with ‘higher better.’ Thirty participants were asked to perform two types of comparison tasks: single-attribute and overall-attribute comparisons. We measured the completion time, error rate, and perceived difficulty of the comparison tasks. The results of the study suggest that, for overall-attribute comparisons, the inverting stacked bar chart was the most effective with regards to the completion time. The results also show that performing overall-attribute comparisons using the classical and diverging stacked bar charts required more time than performing single-attribute comparisons using these charts. Participants perceived the inverting and diverging stacked bar charts as easier-to-use than the classical stacked bar chart for overall-attribute comparisons. However, for single-attribute comparisons, all chart types delivered similar performance. We discuss how these findings can inform the better design of interactive stacked bar charts and visualization tools.