Qualitative versus quantitative career interventions

Assessment tools can be split into two broad categories, those of quantitative (number-, test- or survey-oriented, deductive, using mathematical modelling and numerical statistical patterns) or qualitative (relational, narrative, interpersonal, interview-, activity-, and discussion-oriented, using drawing) types. These tools are used to guide our work with clients, assisting us to measure client characteristics such as values, skills, abilities, interests and personality. These two categories also help both the client and ourselves understand how their personal characteristics connect with occupational selection (Swanson & Fouad, 2020). 

Quantitative tools tend to be represented by instruments such as standardised tests, measuring traits, counting and grouping interests; therefore, the psychometric properties of validity, reliability and norms hold high importance when considering the use of instruments that fall within this category (see here for more information). To be valid, tests must be normalised and standardised to be sure that the results are consistent over the population that is being assessed. Tests must be able to be taken once, then retaken and obtain close to the same result (test/retest validity; Osborn & Zunker, 2016).  

On the other hand, qualitative tools are non-standardised tools, such as Savickas’ Career Construction interview (CCI), narrative therapy, card sorts and career genograms. Qualitative tools assist when working with diverse clients as they “enliven the career counselling process” (Okocha, 1998, p. 5). For example, genograms - vocational family trees - capture a client’s heritage. This can be immensely useful for exploring family patterns, modelling, and dispelling outdated ideas (Osborn & Zunker, 2016). 

Rather than taking a trait-based, person-fit approach, some theories encourage a relational approach. Career construction theory, or CCT, addresses the needs of a workforce facing challenges  (Savickas, 2013). If we stop to think about how much the world has changed in recent years, it is easy to see how technology, rationalisation, redundancy, up-skilling, has resulted in 'new' roles: who would have thought of a "Work-from-home facilitator" pre-Covid? (Kelly, 2021). With CCT, the practitioner utilises 'life design' processes such as story-telling and self-construction techniques, taking either a group or individual approach (Maree, 2019). Career Construction enables clients to build their view of self “from the inside out,” rather than from the outside in, as trait theory prescribes (Savickas, 2013, p. 182). Research seems to indicate that a more relational approach builds greater adaptability and resilience (Savickas, 2013). Practitioners applying this approach may choose to use quantitative assessments - such as values inventories - or not, as best suits each client.

The main thing is that tools should not channel us or our clients: they should assist the client get to know themselves better, and to assist the client to make good quality choices. 

Sam

References:

Kelly, J. (9 May 2021). 10 Hot, Fast-Growing Jobs For The Future Post-Pandemic World. Forbes. https://www.forbes.com/sites/jackkelly/2021/05/19/10-hot-fast-growing-jobs-for-the-future-post-pandemic-world/?sh=f7d44ad5d064 

Maree, J. G. (Ed.). (2019). Handbook of Innovative Career Counselling. Springer.

Okocha, A. A. (1998). Using qualitative appraisal strategies in career counseling. Journal of Employment Counseling, 35(3), 151-159. https://doi.org/10.1002/j.2161-1920.1998.tb00996.x

Osborn, D. S., & Zunker, V. G. (2016). Using Assessment Results for Career Development (9th ed.). Cengage Learning.

Savickas, M. L. (2013). Career Construction Theory and Counseling Model. In S. D. Brown & R. W. Lent (Eds.) Career Development and Counseling. Putting Theory and Research to Work (2nd ed.). John Wiley & Sons.

Swanson J. L., & Fouad, N. A. (2020). Career Theory and Practice: Learning through case studies. Sage Publications, Inc.

read more "Qualitative versus quantitative career interventions"

Qualitative vs Quantitative research

It is always interesting to consider what different authors consider are the differences between qualitative and quantitative research.

Padgett (1998) considers the key distinctions between the two methodological approaches, and sets out the key characteristics of qualitative research as being:

• "Inductive" (p. 3) is being data-led, allowing the data to spring from the findings (Braun & Clarke, 2013), which Padgett suggests seeks to discover theory but not to test existing theory (1998). Inductive research amplifies the findings from "observed cases to [...] other, unobserved, cases or [...] to [...] cases of the same kind" (Jupp, 2006, p. 146).
• "Naturalistic inquiry, in vivo" (Padgett, 1998, p. 3). This refers to a broad group of qualitative methods and approaches, which Padget terms a 'family'; where some members get on much better, including "ethnography, grounded theory, narrative analysis, constructivism, phenomenology, cultural studies, [and] postmodernism" (1998, pp. 1-2), than with others. Think non-laboratory, non-experimental design; think researching a living organism.
• "Uncontrolled Conditions and Open Systems" (Padgett, 1998, p. 3). The lack of control and the open-endedness is due to the inductive nature of the research: this is not a lab experiment where variables can be selected or eliminated. Qualitative research exists in the messy nature of naturalistic inquiry
• "Holistic; Thick Description" (Padgett, 1998, p. 3). This is narrow but rich data, sometimes termed 'an inch wide and a mile deep'. The participant data is complicated, with a lot of internal connections which takes a lot of time to analyse; and there aren't so many participants (Braun & Clarke, 2013). Thick description is the deep, layer upon layer "interpretation [...from the researcher, which is] deeply embedded in the contextual richness" of the participants' lives (Jupp, 2006, p. 300). Think micro-cases contextualising participant lived experience.
• "Dynamic Reality" (Padgett, 1998, p. 3). Methods may grow and evolve as the project rolls out to take account of unexpected findings; plus the method is likely to take longer as - despite planning - effectively qualitative research has to be made up as we go along (Braun & Clarke, 2013)
• "Researcher as Instrument of Data Collection" (Padgett, 1998, p. 3). Qualitative research largely requires "personal involvement and partiality [... so ]subjectivity [and] reflexivity" are key tools which need to be used well (Braun & Clarke, 2013, p. 4)
  
• "Categories Result from Data Analysis" (Padgett, 1998, p. 3). The researcher interacts with the data, seeking "wholes and holes" (Suter, 2011, pp. 348-349), to highlight patterns in our data which we can categorise and then will lead to inductive findings.

What is interesting is that there are two aspects of qualitative research that Padgett does not detail, which are today considered key characteristics. firstly that qualitative research uses words - written or spoken - as data; and secondly that the research results are usually not generalisable, but are about "understand[ing] and interpret[ing] more local meanings; recognis[ing] data as gathered in a context; sometimes produc[ing] knowledge that contributes to more general understandings" (Braun & Clarke, 2013, p. 4).

Whereas quantitative approaches are:

• "Deductive" (Padgett, 1998, p. 3). Springing from a "general model of science" relating to "hypotheses and theories [where] particular occurrences can be deduced and [...from that deduction, then] predicted and explained" (Jupp, 2006, p. 138). Tends to test theory, rather than create it (Braun & Clarke, 2013)
• "Scientific Method/Decontextualizing" (Padgett, 1998, p. 3). This approach is about creating distance and objectivity so that measurement of specific, selected variables can take place
• "Controlled Conditions with Closed Systems" (Padgett, 1998, p. 3). Padgett suggests that "quantitative research favors a 'closed system' approach where every effort is made to neutralize the effects of the observational context (including the observer)" (1998, p. 2)
• "Particularistic" (Padgett, 1998, p. 3). Selected, targeted research of selected variables or hypotheses
• "Stable Reality" (Padgett, 1998, p. 3). Stripping out variables and context to focus the research solely on the element being examined
• "Standardized Data Collection Instruments" (Padgett, 1998, p. 3). Further reducing variation
• "Categories Precede Data Analysis" (Padgett, 1998, p. 3). Determining coding, categories and analysis tools in the planning, prior to commencing the research.

The idea is that the 'heart' of qualitative research is "a bricolage, a pieced-together, tightly woven whole greater than the sum of its parts" (Padgett, 1998, p. 3).

It is always interesting to examine the differences between the two schools of thought.

Sam

References:

• Braun, V., & Clarke, V. (2013). Successful Qualitative Research: A practical guide for beginners. SAGE Publications Ltd.
• Jupp, V. (2006). The SAGE Dictionary of Social Research Methods. SAGE Publications Ltd
• Padgett, D. K. (1998). Qualitative Methods in Social Work Research: Challenges and rewards (Vol. 36, p. 3). SAGE Publications, Inc.
• Suter, W. N. (2011). Introduction to Educational Research: A Critical Thinking Approach. SAGE Publications, Inc.

read more "Qualitative vs Quantitative research"

Research Design: qualitative versus quantitative

Our research design is the spirit in which we will make our decisions about the type of data we will collect. It needs to fit with our research philosophy, and fit with our research method, or methods. Some people call this a research strategy, but I know it as the research design.

The research design falls largely into two main clusters: qualitative, or quantitative, or a combination of both, as follows (McLeod, 2008; Veal, 2005):

1. Qualitative strategies, which look for behaviour (eg, inductive, word, image, sound or video coding, interview, focus group, ethnography, action research)
2. Quantitative strategies, which look for numerical statistical patterns (eg, deductive, survey, experimental approaches, mathematical modelling, SPSS)
3. Mixed methods strategies, using some of each (e.g., cross-sectional, cross-sequential or longitudinal studies)

Qualitative data sources include journals, unstructured observations, paintings, film stock, written records, images, historical accounts, reflections, diaries or recordings. It is more normal to take a descriptive approach - to explore feelings, impressions, what is not said, along with what is said, tone, pace and thematic responses - with qualitative data. Because of there being so many more variables than with quantitative data, qualitative data is harder to analyse (McLeod, 2008; Veal, 2005). Thematic analysis using codes - looking for themes within our data set and marking where a theme repeatedly occurs - is a fairly normal way of analysing qualitative data.

Where we have a small data set, qualitative research can be useful. It allows us to explore in depth how people think or feel - using case studies, interviews, focus groups and surveys yielding textual data - and be able to draw some conclusions. However, generalisability is a problem with qualitative studies, as is researcher bias. It can also take quite a long time to gather our data when undertaking qualitative study, as we are dealing with human subjects, and need to take our time to collect good quality data.

Normally, an inductive inquiry strategy is used with a qualitative research design (or qualitative data). It would also be normal to use a subjective research philosophy.

Quantitative data is usually a numeric measure that yields something which can be counted, ranked, categorised, graphed, or statistically analysed using a range of techniques and processes. Sources come from experiments, lab tests, surveys (yielding numerical data) or structured observations. Normally, an deductive inquiry strategy is used with a quantitative research design (or with quantitative data), and an objective research philosophy.

Hopefully that makes the difference between qualitative and quantitative research designs clear!


Sam

References:

• Creswell, J. (2009). Research Design (Third Edition). USA: Sage
  
• McLeod, S. A. (2008). Qualitative vs. Quantitative. Retrieved 7 July 2017 from https://www.simplypsychology.org/qualitative-quantitative.html
• Veal, A. J. (2005). Business Research Methods (Second Edition). Australia: Pearson Education

read more "Research Design: qualitative versus quantitative"