Text mining as a method for examining the alignment between educational outcomes and the workforce needs

Abstract

Original Research intRoDuction Curriculum redesign is permeating health professions' education amid rapidly changing healthcare practice. [1,2] Embedded in the challenge of curriculum redesign is understanding the job to be done by practitioners in today's healthcare system. [3] As educators work to align curricula with healthcare practice, they must first determine what knowledge and skills students need to be successful in the workplace. In pharmacy, educators have applied various research methodologies to identify core competencies for students. These methods have relied largely on published literature, personal experiences, and academic perspectives to determine pharmacy curriculum outcomes. [4-9] The Academic Affairs Committee of the American Association of Colleges of Pharmacy (AACP) derived entrustable professional activities (EPAs) for pharmacy graduates by brainstorming common activities of pharmacists, consolidating them into a comprehensive list of EPAs, and asking stakeholders to vet them. [4,5] Similarly, McLaughlin et al. used qualitative research methods to facilitate and analyze discussions between pharmacy preceptors, residents, and faculty to "identify the job to be done by pharmacists as integral members of the healthcare team." [7] Job descriptions are another source of data that could be used to determine aspects of pharmacy practice most commonly emphasized by employers. Other disciplines, such as library science and engineering, have used job descriptions to inform curriculum design and student support services. [10-12] Clyde, for example, performed a content analysis of job descriptions to identify librarian competencies and then ensured those skills were being developed through the library curriculum. [10] In addition, Hartmann and Jahren used job posting data to characterize the use of the word "leadership" in an effort Introduction: Job descriptions outline competencies employers consider requisite for success and can be used to inform curriculum design. This paper demonstrates the use of text mining to determine the extent to which key educational outcomes align with job descriptions. Methods: Eighty pharmacist job descriptions containing a total of 12,064 words were text mined using the "bag of words" method. Results: A majority of the 20 most frequent job description words were also present in the pharmacy accreditation standards and American Association of Colleges of Pharmacy entrustable professional activity statements. However, several top 20 words were not, including customer, dispense, department and company. Chi-squared tests revealed text differences between community and health-system pharmacy, including patient, manage, information, and customer, which may have implications for pharmacy schools preparing students for various practice settings. Conclusion: The methodology described here provides a feasible and efficient approach to analyzing current workforce expectations and mapping them to educational outcomes.

Utilising the potential of job postings for auditing learning outcomes and improving graduates' chances on the labour market

“…Text‐mining methods are partially derived from earlier structured data exploration analyses (data mining) and partially from the field of natural language processing. This method was successfully used to detect current job market skills and requirements in job postings for industrial engineers (Darabi et al, 2018), R&D sector (Maer‐Matei et al, 2019), IS Graduates (Föll et al, 2018); so‐called ‘green jobs’ (Janser, 2018), medicine (McLaughlin et al, 2018), as well as generally for analysing skills expected by the labour market (Deming & Kahn, 2017).…”

Which skills are the most prized? Analysing monetary value of geographers’ skills on the labour market in six European countries

“…In addition, compared to point-in-time snapshots provided by survey-based labour market data, which rely on random sampling, these data provide knowledge about changing demands over time and space and, thus, can underpin labour market forecasts (e.g. Clyde 2002;Kopf et al 2012;Carnevale et al 2014;Kim, Angnakoon 2016;Karakatsanis et al 2017;McLaughlin et al 2018). Nowadays, nearly 80-90% of openings that require at least a bachelor's degree are posted online (Carnevale et al 2014;Kureková et al 2015).…”

Exploring the use of ChatGPT to analyze student course evaluation comments

“…In parallel with the development of ChatGPT, the field of text analytics (e.g., text mining) has been steadily evolving within higher education [4,5]. Text mining has been employed to increase faculty efficiency by extracting valuable insights from vast quantities of text-based materials, such as student reflections and preceptor comments [6,7].…”