Overcoming Obstacles: The Power of Attitude in Enhancing Wellness and Learning
Through a recent study conducted in the US, we explored how learners from two groups, namely (i) Higher Education Learners (ie. college) and (ii) Informal Learners (ie. adults working towards a specific diploma, certification, or on their own), performed in terms of wellness and learning.
For the purpose of our analyses, our definition of wellness included mental factors (eg. anxiety, depression, isolation, etc.), social factors (eg. access to external support), and physical factors (eg. sleep, diet, exercise, etc.). To analyze learning, we used several dimensions such as motivation, time available, access to mentorship, grit, and depth of learning, among others.
Through a 1,000-responder survey that evaluated more than 25 distinct dimensions of wellness and learning, we uncovered three distinct student segments, each characterized by a unique combination of wellness and learning attributes. Most interestingly, we were able to identify that the extent to which students were “feeling discouraged when facing challenges or setbacks” was a key determinant and potential predictor of a student’s own segment.
A Tripartite Division: Wellness and Learning Personas
Informed by a thorough review of more than 48 peer-reviewed articles and reports, we created a list of the most common barriers, drivers, and habits of both wellness and learning. We then conducted 25 one-on-one interviews with learners in the US (14 college students and 11 informal learners) to refine the list and develop the key hypotheses to test in the larger quantitative study. When ready, we launched a survey that captured the viewpoint of over 1,000 learners (50% college and 50% informal) in the US.
The survey evaluated the barriers, drivers, and habits of both wellness and learning by presenting sentences to the respondents and asking them to declare their level of agreement or disagreement using a 5-scale Likert scale. This allowed us to have a numerical score for each sentence. Then, we leveraged machine learning techniques to process the survey data and uncovered three distinct student segments:
- High wellness and high learning (the students who seem to thrive in the current system): This group represents students whose wellness and learning scores are high. This leads us to believe that this group thrives in the current system as they are able to maintain superior levels of physical, social, and mental wellness while also reporting high scores for learning drivers and habits.
- Moderate wellness and moderate learning (the “middle of the pack”): Occupying the middle ground, these students display average levels of both wellness and learning. This group seems to be able to balance their learning with their well-being, although not excelling in either.
- Low wellness and low learning (the students who seem to struggle in the current system): This segment includes students who reported low scores in both wellness and learning dimensions. This leads us to believe that the currently available learning alternatives are not well suited for them as they are scoring low in learning drivers and habits while also reporting low levels of overall wellness.
About the Author
Hector Alvarado
Hector Alvarado is a Director at The Decision Lab. He holds a Masters in Applied Statistics from the University of Oxford, an MBA from INSEAD and a Bachelors in Actuarial Science. He is very interested in applying insights and his past experience to generating meaningful impact for vulnerable populations around the globe. Prior to joining The Decision Lab, Hector worked about 5 years as a Private Equity investor in the Infrastructure Sector in LATAM and over 6 years as a Management Consultant with the Boston Consulting Group. Hector has lead large transformation, growth strategy and integration projects in the Pharma, Consumer Goods and Banking Industries both in North and Latin America.
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