CGC/STUDY Opening

Science Research · IRB-approved study

Career
Goal
Clarity

Do students who know where they're headed show up differently in school? And can one evening with real professionals make the path clearer?

2
connected studies
4
anonymous surveys
60
minute career night
11
published sources

Derek Graffeo · Grade 11

What you're seeingThousands of points with no shared direction. This is where many students start: lots of options, no clear path. Press → to begin.

01 · Why it matters

Every choice opens a door and closes others

Schools ask students to choose courses before most of them know where they're headed. Math is the clearest example: at many high schools, the course you start in grade 9 decides whether calculus is reachable by grade 12.

Starting in Algebra 1 leads to Precalculus by grade 12. AP Calculus closes unless you add a summer course or double up on math.

What you're seeingEach door is one math course, from grade 9 (left) to grade 12 (right). Lit doors are still reachable from the choice you made, and dark doors have closed. The violet path is the hard way back. Course sequences vary by school; this is one common pattern.

02 · The idea

Choose with the map in hand

2 in 5

15-year-olds across OECD countries had no clear career plans in 2022, up by more than half since 2018. OECD, 2024

The doors keep coming: electives, AP courses, majors. Stepping down is easy and climbing back up is hard, so the time to get informed is before the choice, not after.

What you're seeingThe whole web of school choices in 3D. Every fork is a decision. The amber branch is one route taken on purpose, from grade 9 to a career, by a student who knew where they were heading.

03 · The questions

Two questions, one thread

RQ1

What is the relationship between career goal clarity, academic motivation, and academic engagement, and does it differ between underclassmen and upperclassmen?

RQ2

To what extent does career goal clarity change after a structured career exposure program?

What you're seeingTwo orbits, one per question. Each pulls around its own core, and both cores are career goal clarity.

04 · What gets measured

Three variables

Career goal clarity
How clearly a student understands their future career goals and direction.
Marciniak et al., 2021
Academic motivation
Why a student wants to take part in school and succeed.
Vallerand et al., 1992
Academic engagement
How actively a student takes part in class, in behavior and emotion.
Skinner et al., 2009

What you're seeingOne sphere per variable. The study looks at the overlap, where all three meet.

05 · Hypotheses

What I expect to find

  1. H1Students with clearer career goals will report higher motivation and engagement. The link may be stronger in grades 11–12, closer to career-shaping decisions.
  2. H2Career goal clarity will be higher after Career Exposure Night than before it.

What you're seeingA 3D plot with one axis per variable. Each glowing cluster is one imagined student. If H1 holds, students climb all three axes together. This is an illustration, not data.

06 · Study design

Two connected studies

Study 1

General survey

Open to any student in grades 9–12. Measures clarity, motivation, and engagement, then compares grades 9–10 with 11–12.

Study 2

Pre / post

Career Exposure Night participants answer the same clarity questions before and right after the event. Compared as group averages.

What you're seeingLeft: everyone in Study 1, split by grade band. Right: Study 2, where the faint outer shell is "before" and the bright core is "after".

07 · The intervention

Sixty minutes, built to scale

  1. 00–10Introduction to the career field and the professionals
  2. 10–25Career presentations: education, path, daily work
  3. 25–40Professional discussion: skills, challenges, advice
  4. 40–55Student questions
  5. 55–60Career-planning reflection

What you're seeingEach block's length is its share of the hour. Every participant gets the same program, so there is no control group.

08 · Protecting participants

Anonymous by design

  • Parent or guardian consent before any student under 18 takes part
  • Student assent before the survey opens
  • No names, emails, or school names collected
  • Consent records stored apart from answers
  • Skip any question, or stop at any time
  • Results reported only as group totals and averages

What you're seeingGuard rings for consent, assent, and anonymity circle the answers at the center. Nothing that identifies a student gets inside.

09 · Results

What the data shows

Awaiting data

Results appear here once the survey data is analyzed. Nothing is shown until then, so every number in this presentation will be real.

  • rClarity and motivation
  • rClarity and engagement
  • ΔClarity, before vs. after

What you're seeingAn empty ring. It turns into bars of real before and after averages once the data is analyzed.

10 · Student voices

What students wrote

Awaiting analysis

Themes from students' written feedback about Career Exposure Night will appear here after a thematic analysis. Only themes and counts are shown, never anything that could identify a student.

What you're seeingFaint clusters waiting for themes. After analysis, each cluster is one theme, and its size is how many responses mention it.

11 · Research log

Where the project stands

    What you're seeingThe project's timeline. The lit path is finished work, and the pulsing node is in progress right now.

    12 · Next

    From scattered to focused

    If the findings support the hypotheses, they will shape a career-education website, model classroom units, and curriculum materials for schools in the Westchester area.

    What you're seeingThe scattered field from the first slide, focused into one beam. That's the goal of the whole project.

    Sources (11)
    1. Azhenov, A., Kudysheva, A., Fominykh, N., & Tulekova, G. (2023). Career decision-making readiness among students in the system of higher education: Career course intervention. Frontiers in Education, 8, 1097993. doi
    2. Creed, P. A., Prideaux, L.-A., & Patton, W. (2005). Antecedents and consequences of career decisional states in adolescence. Journal of Vocational Behavior, 67(3), 397–412. doi
    3. Hirschi, A. (2009). Career adaptability development in adolescence. Journal of Vocational Behavior, 74(2), 145–155. doi
    4. Lent, R. W., Brown, S. D., & Hackett, G. (1994). Toward a unifying social cognitive theory of career and academic interest, choice, and performance. Journal of Vocational Behavior, 45(1), 79–122. doi
    5. Lounsbury, J. W., Hutchens, T., & Loveland, J. M. (2005). Big Five personality traits and career decidedness among early and middle adolescents. Journal of Career Assessment, 13(1), 25–39. doi
    6. Marciniak, J., Hirschi, A., Johnston, C. S., & Haenggli, M. (2021). Measuring career preparedness among adolescents: The Career Resources Questionnaire—Adolescent Version. Journal of Career Assessment, 29(1), 164–180. doi
    7. OECD. (2024). Teenage career uncertainty: Why it matters and how to reduce it. OECD Education Spotlights, No. 16. doi
    8. Skinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009). A motivational perspective on engagement and disaffection. Educational and Psychological Measurement, 69(3), 493–525. doi
    9. Vallerand, R. J., Pelletier, L. G., Blais, M. R., Brière, N. M., Senécal, C., & Vallières, E. F. (1992). The Academic Motivation Scale. Educational and Psychological Measurement, 52(4), 1003–1017. doi
    10. Wang, D., Li, Y., & Wang, G. (2024). A systematic review on career interventions for high school students. Frontiers in Psychology, 15, 1461503. doi
    11. Whiston, S. C., Li, Y., Goodrich Mitts, N., & Wright, L. (2017). Effectiveness of career choice interventions: A meta-analytic replication and extension. Journal of Vocational Behavior, 100, 175–184. doi