Academic journal article Quarterly Review of Distance Education

EMERGING EVIDENCE ON THE USE OF BIG DATA AND ANALYTICS IN WORKPLACE LEARNING: A Systematic Literature Review

Academic journal article Quarterly Review of Distance Education

EMERGING EVIDENCE ON THE USE OF BIG DATA AND ANALYTICS IN WORKPLACE LEARNING: A Systematic Literature Review

Article excerpt

INTRODUCTION

Charities, nonprofits, and international nongovernmental organizations (iNGOs) recognized early the potential of distance learning to help develop staff competencies in business critical areas. This is especially true for international organizations with staff and offices located in various, geographically separated parts of the globe. For example, the World Wide Fund for Nature started its blended learning Conservation Leadership Program in 1998 (Stoel, 2004), far earlier than many corporate universities began seriously considering online learning as an educational option. Even for those organizations with fewer resources than one such as the World Wide Fund for Nature, there exist several interorganizational initiatives to increase access to available online learning. One example is the Cornerstone OnDemand Foundation, which has a distance learning course library that is freely available on the disasterready.org website (Cornerstone OnDemand Foundation, 2016). Another example is LINGOs, a membershipdriven organization, which offers a complimentary learning management system for members as well as access to Last Mile Learning, a distance learning library with courses on financial management, people management, and project management (Last Mile Learning," 2016; LINGOs, 2016).

Such nonprofit organizations are no strangers to the use of data to guide relief, development, fundraising, and marketing efforts. For example, in marketing and fundraising efforts, data analysts are essential resources to determine what different audiences are interested in (e.g., types of programs) or to measure the effectiveness of a specific campaign (Toal, 2014). In addition, large amounts of data are gathered in program delivery within such organizations. For example, humanitarian organizations use technology to register individuals affected by disasters and better manage certain services that are offered to them (Chibafa, 2014). Additionally they can be used to create end-to-end visibility in their supply chain data (Helios Foundation, 2014). That being the case, we hypothesized, would it not make sense for such organizations to analyze if and how performance improvement, including staff development programs, resulted in operational gains?

Having observed such examples in the authors' combined 17 years of experience working in performance improvement, training, distance education, and capacity building initiatives in nongovernmental organizations (NGOs) and iNGOs, we were interested to determine to what extent learner analytics are driving management decisions about such initiatives. We also were interested in determining the potential uses of "big data" (to be defined below) and analytics to improve the practice of instructional designers and learning and development project managers.

A systematic review of recognized academic publications yielded very few results (specifically, one) on our primary research question. While there were examples that big data are being employed in nonprofit organizations (e.g., the United Nations), the use of big data in projects focusing on training and development were almost nonexistent in the literature. Therefore, the review was broadened in scope to the use of big data and analytics in workplace learning, performance improvement, and learning and development in business and governmental settings. This broadening of scope yielded a greater number of documents covering our topic, and therefore serves as the basis for this literature review.

We describe this literature review as a systematic literature review of how big data and analytics are currently being used in institutionally based formal workplace learning, talent development initiatives, and training departments. Additionally, we examine why many organizations are not yet analyzing their own big data, and what resources are required to begin utilizing big data and analytics to improve outcomes, minimize costs, increase revenue, and achieve strategic business outcomes for the typical organization. …

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