Future Dreaming 2024 | Digital technology in transitions "The experience of CLAP@JC in Hong Kong"

This presentation from the OECD Future Dreaming 2024: Career Guidance in the Age of Digital Technologies looks at digital technology in transitions "The experience of CLAP@JC in Hong Kong". Presented by Steven Ngai Sek-yum and Brian Cheng.

Discover the videos and other sessions from the OECD Future Dreaming 2024 conference at https://www.youtube.com/@EduSkillsOECD

Find out more about our work on Career Readiness https://www.oecd.org/en/about/projects/career-readiness.html

1. Digital Technology in Transitions: The Experience of CLAP@JC in Hong Kong Created and funded by: Steven Ngai Sek-yum Director & Principal Investigator, CLAP@JC Brian Cheng Director (Business), CLAP@JC

2. Acknowledgements Page 2 The study was derived from part of a larger evaluation study of the CLAP@JC Project created and funded by The Hong Kong Jockey Club Charities Trust. CLAP@JC is a trust-initiated project and a cross-sectoral support platform on career and life development (CLD), aiming to foster a sustainable ecosystem by bringing together the education, business, and community sectors to smoothen the transition from school to work for all youth. The project encourages youth to “Live Differently, Live Fully” and maximize their endless potential through setting sail on a unique life journey. For more information, please visit https:// clap.hk /.

3. Why do we need an intervention for youth in Hong Kong?

4. Introduction School-to-work transition The period and process during which graduates leave school and enter the labor market (Phillips et al., 2002; Zamfir et al., 2018) Make decisions that determine their later vocational outcomes and establish future career and life patterns (Ng & Feldman, 2007; Saks, 2018) Crucial phase for young people Difficulties in school-to-work transition L ow life satisfaction (Kinicki et al., 2000) I ncreased physical and psychological strain (Cheng-Lai & Dorcas, 2011; Huegaerts et al., 2018) H igh risk of being stuck in unemployment, underemployment, or unstable employment (Koen et al., 2012; Park et al., 2020) Suffering from a myriad of adverse consequences, including low well-being (McKee-Ryan & Harvey, 2011) M acro-socioeconomic level: I ncreased antisocial behaviors and thus increase social costs ( Medvide et al., 2019; Saks, 2018) Individual level: Page 4

5. Introduction Economic globalization and advanced technology Uncertainty and unpredictability (Ngai et al., 2021; 2022) M ore tortuous, longer, and less controllable school-to-work transition (Allen & Van Der Velden, 2007; Morrison, 2002; Ryan, 2001) COVID-19 pandemic Hong Kong: from February to April 2022 U nemployment rates for 15–19 and 20–29 years old were 17.2% and 7.7%, respectively Outpaced the overall unemployment rate of 5.5% during the same period (Census and Statistics Department, 2022) Non-engaged youth (NEY) More vulnerable than their peers A t risk of becoming NEET youth (Mo & Lau, 2020; Ngai & Ngai, 2007) May include…. E thnic minority youth U nemployed youth S chool dropouts Y outh offenders Y outh with special education needs Y oung mothers (Ngai et al., 2023) Page 5

6. Our intervention model and artefacts under CLAP@JC

7. CLAP@JC aims to foster a sustainable ecosystem by bringing together the education, business, and community sectors to smoothen the transition from school to work for all youth. The project will introduce a systemic framework “CLAP@JC HK Benchmarks”, empowering schools to build quality CLD provisions for students. In community and workplace, the CLD-driven intervention will be promoted in mainstream youth services and pre-employment trainings. We envision all youth to be able to achieve meaningful lives and aspire to make positive contributions to society . What is CLAP@JC? Page 7

8. Page 8 Page 8

9. Page 9 Page 9

10. CV360 – Transition to Employment 2. Consolidate non-paid and paid experience 3. Match VASK with respective experience for self-understanding Unleashing possibilities on Career and Life Development (CLD) journey Through reviewing CLD journey, youths could see what they have learnt and explore multiple pathways [email protected] [email protected] Effective talent-matching It reflects users’ personal quality gained / discovered from different life experience, which allows employers to understand young employees’ strengths and interests comprehensively. 1. Select a template 4. Fill in other info and a CV360 is built How CV360 help transition to employment? Page 10

11. VASK Test 1. How do you spend free time during holiday? 2. Which of the following characters is your favourite ? 3. Which of the following animals can best describe you? 4. Which position you are good at when you are working in a team/group? 5. Which kind of TV programme is your favourite ? 1 st step 2 nd step 3 rd step *a VASK card is generated for youth’s self-understanding Page 11

12. ENOW Mobile Game App Takes on different mini-games; challenge yourself or compete with friends to achieve the daily highest score Explore VASK in the library In members area, youths can accomplish various missions designed by social workers related to their Career and Life Development (CLD) goals It provides a more interactive and interesting way for youths to understand more concepts of Career and Life Development (CLD) Page 12

13. Right Talent to Right Position Enhancing the effectiveness of talent matching, job position recruitment with using VASK can provide an all-round profile for understanding the job nature Build up VASK portfolios for each job category, and match them with the VASK of participating young people Job & VASK Data Bank Promoting VASK facilitates transition to employment Page 13

14. The overarching impact of CV360 Page 14 Broadening the definition of talent : talent pool talent is no longer defined by purely exam scores but instead competence and potential for development Better talent match : both youth and businesses are clear of what are needed to be successful with mutual understanding and expectation aligned. The use of VASK is beyond recruitment but also on coaching, job assignment, appraisal and staff development More productive and happier workforce : better match with ability, aspiration and values between youth and businesses Contribute to fairer society that promotes upward mobility : youth are able to engage with the world of work with greater sense of hope

15. Quantitative Impact of CLAP@JC Digital Interventions

16. Changes in Youth Career Development Competency (YCDC) from T1 (Month 0) to T2 (Month 4) & T3 (Month 16) (Intervention Group: n = 378, Control Group: n = 252)

17. Means of YCDC between Intervention and Control Groups at T1, T2 and T3 Page 17

18. Repeated MANCOVA Analysis on the Effects of Digital Interventions on YCDC and Its Sub-dimensions Page 18 　 Control Group (Mean) Intervention Group (Mean) T2 vs T1 T3 vs T1 　 T1 T2 T3 T1 T2 T3 η p 2 η p 2 YCDC 3.321 3.169 3.273 3.287 3.470 3.503 0.011*** 0.016*** Engagement 3.288 3.091 3.224 3.209 3.357 3.482 0.013*** 0.022*** Self-understanding 3.367 3.195 3.342 3.325 3.429 3.620 0.009** 0.012*** Career & Pathway Exploration 3.174 3.119 3.237 3.062 3.262 3.465 0.007** 0.014*** Planning & Career Management 3.261 3.143 3.272 3.183 3.291 3.524 0.006** 0.013*** Note: Covariates controlled: Age, Gender (dummy variable), Education Level (dummy variables), whether born in Hong Kong (dummy variable), and whether r eceiving P ublic A ssistance (dummy variable). * p<0.05, ** p<0.01, *** p<0.001.

19. Changes in Career and Life Development Hope (CLDH) from T1 to T2 & T3

20. Means of CLDH between Intervention and Control Groups at T1, T2 and T3 Page 20

21. Repeated MANCOVA Analysis on the Effects of Digital Interventions on CLDH and Its Sub-dimensions Page 21 Note: Covariates controlled: Age, Gender (dummy variable), Education Level (dummy variables), whether born in Hong Kong (dummy variable), and whether r eceiving Public Assistance (dummy variable) . * p<0.05, ** p<0.01, *** p<0.001. 　 Control Group (Mean) Intervention Group (Mean) T2 vs T1 T3 vs T1 　 T1 T2 T3 T1 T2 T3 η p 2 η p 2 CLDH 2.971 2.971 3.069 3.041 3.327 3.364 0.012** 0.005* CLDP 2.397 2.580 2.861 2.535 2.872 3.080 0.008*** 0.003 CLDA 3.219 3.173 3.324 3.150 3.393 3.427 0.019*** 0.004*

22. Changes in Career Adaptability (CA) from T1 to T2 & T3

23. Means of CA between Intervention and Control Groups at T1, T2 and T3 Page 23

24. Repeated MANCOVA Analysis on the Effects of Digital Interventions on CA and Its Sub-dimensions Page 24 Note: Covariates controlled: Age, Gender (dummy variable), Education Level (dummy variables), whether born in Hong Kong (dummy variable), and whether r eceiving Public Assistance (dummy variable) . * p<0.05, ** p<0.01, *** p<0.001. 　 Control Group (Mean) Intervention Group (Mean ) T2 vs T1 T3 vs T1 　 T1 T2 T3 T1 T2 T3 η p 2 η p 2 CA 3.611 3.566 3.614 3.609 3.712 3.733 0.004** 0.002** Concern 3.411 3.375 3.568 3.378 3.544 3.676 0.002* 0.001* Control 3.659 3.631 3.664 3.664 3.719 3.812 0.002* 0.004* Curiosity 3.615 3.541 3.615 3.602 3.675 3.744 0.004*** 0.002*** Confidence 3.577 3.501 3.552 3.540 3.654 3.686 0.008* 0.004*

25. Sequence Analysis of Transitional Trajectories from Month 0 to Month 16 (Intervention Group: n = 579, Control Group: n = 323)

26. The Transversal State Distribution of Clusters of the Non-engaged Youth’s Life Trajectory Page 26 Month Month Month 1 3 4 Month 5 2

27. Case Distribution and Predicted Probabilities of the Clusters Page 27   Descriptive Distribution   Predictive Probabilities     (%)   (95% CI)   Control Group Intervention Group   Control Group Intervention Group   D=I-C   C1: Employment / Entrepreneurship 317   0.00 0.51 0.51*** 0.00% 54.75%   [0.00, 0.03] [0.47, 0.55]   C2: Vocational Education & Training 38 77   0.11 0.16 0.05*** 11.76% 13.30%   [0.03, 0.19] [0.14, 0.18]   C3: Generic Education 22 66   0.08 0.11 0.02* 6.81% 11.40%   [0.05, 0.11] [0.08, 0.13]   C4: Serious Leisure Development 53 119   0.19 0.22 0.03* 16.41% 20.55%   [0.15, 0.24] [0.189, 0.25]   C5: NEET 210   0.62 0.00 -0.62*** 65.02% 0.00%   [0.60, 0.65] [0.00, 0.03]   Total 323 579       Note: * p<0.05, *** p<0.001. Age, Gender (dummy), Education L evel (dummies), whether born in Hong Kong (dummy), and whether receiving Public Assistance (dummy) were included as control variables in the multinomial logistic regression.

28. Qualitative Impact of CLAP@JC Digital Interventions

29. Enhancing Self-Understanding and Career Readiness Case Example 1: I nstitutionalized youth using CV360 to present his all-round profile and secure an internship and later an employment opportunity in a design company CV360 has enabled me to deepen my self-understanding while also allowing me to showcase my strengths. (Youth 1) CV360 is invaluable, enabling youth to create unique resumes and serving as a highly effective tool in career guidance. (Social Worker 2) CV360 helps youth recognize their strengths, increase self-confidence, and enhance employment opportunities and competitiveness . (Social Worker 1) Case Example 2: CV360 facilitating meaningful encounters between young people and employers/community mentors during a career fair, enhancing career readiness Page 29

30. Page 30 Broadening the definition of talent and better talent matching "In the past, we hired only University graduates. We had difficulties finding the right talents. After partnering with CLAP@JC, CV360® provides a more comprehensive picture from general CVs. With youth providing their different paid and unpaid experiences, we it facilitates our talent matching process by seeing the youth’s personal characteristics m ore comprehensively ." Mr. Ricky Ma General Manager of Human Resources AsiaWorld -Expo ” With the support of CV360® and VASK, youth are more positive and passionate about the career that they are going for, and we could be more direct in unpacking their personal experience and assess the suitability. The concept of VASK has been incorporated in our talent development process, which helps us develop and nurture our talents." Ms. Joyce Mak Director of Talent Acquisition KBQuest Hong Kong Limited ”The youth from CLAP@JC demonstrate strong capabilities in technical skills, as well as proactiveness in learning new skills which create value for the company. We used to hire master degree graduates in our company, but having the chance to work with CLAP@JC and CV360®, we have broadened our definition of talents and also a bigger talent pool for the industry." Mr. Jack Ng Head Beta Labs @ Lane Crawford Joyce Group Peter Ng From a hidden youth for 4+ years to a data engineer Data Engineer, Beta Labs @ Lane Crawford Joyce Group Gary Chung From a sales to a graphic designer to a data engineer Ex-Data Engineer, KBQuest Continued his career on a data project in a local University Thomas Wong From a high school drop-out to a Customer Service Associate Customer Service Associate, AsiaWorld -Expo

31. Page 31 References Allen, J., and Van Der Velden, R. (2007). “Transitions from higher education to work,” in Careers of University Graduates , ed U. Teichler (New York, NY: Springer), 55–78). Census and Statistics Department. (2022). Unemployment rate by sex by age. https:// www.censtatd.gov.hk / en / web_table.html?id =11 Cheng-Lai, A., and Dorcas, A. (2011). Learning and psychological difficulties among non-engaged youth in Hong Kong. Int. J. Disabil . Hum. Dev. 10, 235–240. doi : 10.1515/ijdhd.2011.034 Huegaerts , K., Spruyt , B., and Vanroelen , C. (2018). Youth unemployment and mental health: The mediating role of embodiment. Societies . 8, 43. doi : 10.3390/soc8020043 Koen, J., Klehe , U. C., and Van Vianen , A. E. (2012). Training career adaptability to facilitate a successful school-to-work transition. J. Vocat . Behav . 81, 395–408. doi : 10.1016/j.jvb.2012.10.003 McKee-Ryan, F. M., and Harvey, J. (2011). “I have a job, but . . .”: a review of underemployment. J. Manage. 37, 962–996. doi : 10.1177/0149206311398134 Medvide , M. B., Kozan , S., Blustein , D. L., and Kenny, M. E. (2019). “School to work transition of non-college bound youth: An integration of the Life Design paradigm and the Psychology of Working Theory,” In Handbook of Innovative Career Counselling , ed J. G. Maree (Cham: Springer), 157–172. Mo, P. K. H., and Lau, J. T. F. (2020). Psychoactive substance use among Chinese non-engaged youth: the application of the health belief model. Child. Youth Serv. Rev . 113, 105008. https://doi.org/10.1016/j.childyouth.2020.105008 Ng, T. W. H., and Feldman, D. C. (2007). The school-to-work transition: a role identity perspective. J. Vocat . Behav . 71, 114–134. doi : 10.1016/j.jvb.2007.04.004 Ngai, S. S. Y., Cheung, C. K., Mo, J., Wang, L., Ng, Y. H., and Wang, P. (2023). Career interventions and social well-being among non-engaged youth: examining the mediating effects of career competency. Child. Youth Serv. Rev . 106903. https://doi.org/10.1016/j.childyouth.2023.106903 Ngai, S. S. Y., Cheung, C. K., Wang, L., Li, Y., Ng, Y. H., Yu, E. N. H., and Leung, W. P. C. (2022). Development and validation of the Career and Life Development Hope (CLDH) Scale among non-engaged youth in Hong Kong. Int. J. Environ. Res. Public Health . 19, 10283. https://doi.org/10.3390/ijerph191610283 Ngai, S. S. Y., and Ngai, N. P. (2007). Empowerment or disempowerment? A review of youth training schemes for non-engaged young people in Hong Kong.  Adolescence.  42(165), 137–149. Ngai, S. S. Y., Wang, L., Cheung, C. K., Mo, J., Ng, Y. H., and Wang, P. (2021). Development and validation of the Youth Career Development Competency Scale: a study based on Hong Kong youth. Int. J. Environ. Res. Public Health . 18, 12494. https://doi.org/10.3390/ijerph182312494 Park, M., Lee, S., Nam, K. C., Noh, H., Lee, S., and Lee, B. J. (2020). An evaluation of the youth employment support program in South Korea: Focusing on the outcome of preventing NEET. Child. Youth Serv. Rev. 110, 104747. doi : 10.1016/j.childyouth.2020.104747 Phillips, S. D., Blustein , D. L., Jobin-Davis, K., and White, S. F. (2002). Preparation for the school-to-work transition: the views of high school students. J. Vocat . Behav . 61, 202–216. doi : 10.1006/jvbe.2001.1853 Saks, A. M. (2018). “Job search and the school-to-work transition,” In The Oxford Handbook of Job Loss and Job Search, eds U. Klehe and E. Van Hooft (Oxford: Oxford University Press), 379–400. Zamfir , A. M., Militaru , E., Mocanu , C., and Lungu, E. O. (2018). School-to-work transition of higher education graduates in four European countries. Compare. doi : 10.1080/03057925.2018.1493572