Before Proposing to Change theEquation, We should Know All the            Variables          Adam V. Maltese           Mar...
Outline• Introduction• Degree production in US• Analysis of longitudinal data• Student interest data• Graphical literacy• ...
Introduction• Focus of recent National policy initiatives  (e.g., Educate to Innovate):  – Increasing performance in STEM ...
Bachelor’s Degrees (1966-2006)                  1,500,000                                                                 ...
Changes in degrees over time  You can access these visualizations to create your own here.
Changes in degrees over time    [BS in Biology 1966-2010]
Changes in degrees over time      [Chemistry1966-2010]
Changes in degrees over time[Bio/Math/CompSci/Engnr: 1966-2010]
Changes in degrees over timeBiology   Math/Stats     Computer Science   Engineering                       1966            ...
Analysis of Longitudinal Data
Previous Findings                 (based on NELS data)• Indicators of “interest” in STEM (e.g.,  Career aspirations, Scien...
Percentage of Students Enrolled in High SchoolMathematics Classes by Major Classification (n=4,700)                       ...
Percentage of Students Enrolled in High School ScienceClasses by Major Classification (n=4,690)                           ...
Samples• NELS = 4,700 with HS transcripts,  completed 20+ college classes & 4-yr Inst.• ELS = 6,040 with HS transcripts an...
Most Common HS Pathways          NELS           ELS          HSTSRank   (1988-1992)   (2000-2004)   (2005-2009) 1     PS-B...
18%
~1%         ELS               NELSPct of STEM Majors Pct of STEM Degrees     B-C-M-M             B-C-M-P    PS-B-PS-B     ...
Analysis of “Switchers”• 60% of ss who indicated interest in STEM  career in 8th grade ended up with major  outside of STE...
MS student interest in science          (Maltese & Tai, 2011)
Interest in STEM jobs                                             35  Student                                           e ...
Impact of standardized testing             (Maltese & Hochbein, 2012)• Used three cohorts of HS students in IN  who partic...
Graphical literacy   (Harsh & Maltese, 2012)
Study Methods• Streams of data collected to investigate how  students and scientists interpret and construct  graphs  Stre...
Impact of REUs/UREs     (Harsh, Maltese & Tai, 2011)  (Harsh, Maltese & Tai, Forthcoming)
What are the indicated benefits of             participation in UREs?                                                  Tot...
Gender Differences in Chemistry and Physics UREs• Male and female participation rates have made equivocal  percentage-wise...
Planned URE Research• Multi-site assessment of URE program variables that  influence short- and long-term outcomes for stu...
Synthesis• Flat growth in STEM degrees (some decline)• Engaging students early appears to be  important, seems that many s...
Adam Maltese - Before Proposing to Change the Equation, We should Know All the Variables
Adam Maltese - Before Proposing to Change the Equation, We should Know All the Variables
Adam Maltese - Before Proposing to Change the Equation, We should Know All the Variables
Adam Maltese - Before Proposing to Change the Equation, We should Know All the Variables
Adam Maltese - Before Proposing to Change the Equation, We should Know All the Variables
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Adam Maltese - Before Proposing to Change the Equation, We should Know All the Variables

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Presented by Adam Maltese at the 67th Annual Meeting of the ORAU Council of Sponsoring Institutions

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Adam Maltese - Before Proposing to Change the Equation, We should Know All the Variables

  1. 1. Before Proposing to Change theEquation, We should Know All the Variables Adam V. Maltese March 14, 2012
  2. 2. Outline• Introduction• Degree production in US• Analysis of longitudinal data• Student interest data• Graphical literacy• Participation in U-grad Research Experiences• Summary
  3. 3. Introduction• Focus of recent National policy initiatives (e.g., Educate to Innovate): – Increasing performance in STEM – Increasing size of STEM workforce• Ratio of STEM degrees to Total degrees in decline over last 40 yrs•Bureau of Labor predicts by 2018 there willbe 2 Million job openings in STEM fields asresult of baby-boomer retirement & new jobs
  4. 4. Bachelor’s Degrees (1966-2006) 1,500,000 End of Cold War 1,250,000 Vietnam WarDegrees Awarded 1,000,000 Dot Com Human Total Degrees Genome 750,000 "bubble" bursts mapped Total STEM STEM (No CS) 500,000 250,000 0 74 98 66 70 78 82 86 90 94 03 19 19 19 19 19 19 19 19 20 19 (Source: NSF, 2008)
  5. 5. Changes in degrees over time You can access these visualizations to create your own here.
  6. 6. Changes in degrees over time [BS in Biology 1966-2010]
  7. 7. Changes in degrees over time [Chemistry1966-2010]
  8. 8. Changes in degrees over time[Bio/Math/CompSci/Engnr: 1966-2010]
  9. 9. Changes in degrees over timeBiology Math/Stats Computer Science Engineering 1966 2010
  10. 10. Analysis of Longitudinal Data
  11. 11. Previous Findings (based on NELS data)• Indicators of “interest” in STEM (e.g., Career aspirations, Science will be useful in my future, Planned major) positively associated with STEM degree• High School Experiences: • Emphasis on learning facts/rules (-) • Emphasis on understanding through use of hands- on materials in math (+) • Emphasis on further study in science (+) • Frequent use of books to do experiments (-) • Frequent use of computers in math (-) • Frequent teacher lectures in science (-)
  12. 12. Percentage of Students Enrolled in High SchoolMathematics Classes by Major Classification (n=4,700) Non-STEM STEM Grade 9 Algebra 65.53 65.26 Geometry 14.23 27.59 Trig/Algebra II <1 1.12 PreCalculus <1 <1 Calculus <1 <1 Grade 10 Algebra 39.24 40.12 Geometry 50.42 48.43 Trig/Algebra II 3.00 7.01 PreCalculus <1 <1 Calculus <1 1.05 Grade 11 Algebra 44.34 39.21 Geometry 20.85 12.88 Trig/Algebra II 14.61 23.97 PreCalculus 11.44 24.18 Calculus 1.63 4.52 Grade 12 Algebra 17.39 10.18 Geometry 6.75 4.10 Trig/Algebra II 13.12 17.21 PreCalculus 16.70 17.96 Calculus 14.05 35.13Note. Proportions do not add to 100 due to students enrolled in multpleclasses. All proportions are significantly different (p<.05), unless italicized.
  13. 13. Percentage of Students Enrolled in High School ScienceClasses by Major Classification (n=4,690) Non-STEM STEM Grade 9 Biology 29.33 34.93 Chemistry <1 <1 Physics <1 <1 Earth Science 13.82 11.11 Grade 10 Biology 66.20 60.12 Chemistry 18.73 27.89 Physics 1.52 2.31 Earth Science 2.07 1.49 Grade 11 Biology 8.22 13.69 Chemistry 55.10 62.17 Physics 11.18 17.56 Earth Science 1.91 <1 Grade 12 Biology 9.11 13.86 Chemistry 10.87 19.80 Physics 25.61 45.10 Earth Science 2.08 <1Note. Proportions do not add to 100 due to students enrolled in multpleclasses. All proportions are significantly different (p<.05), unless italicized.
  14. 14. Samples• NELS = 4,700 with HS transcripts, completed 20+ college classes & 4-yr Inst.• ELS = 6,040 with HS transcripts and indication of declared major• HSTS = 37,500 with HS transcripts collected
  15. 15. Most Common HS Pathways NELS ELS HSTSRank (1988-1992) (2000-2004) (2005-2009) 1 PS-B-C-No PS-B-C-No PS-B-C-No 2 PS-B-C-P PS-B-C-P PS-B-C-B 3 PS-B-C-B B-C-P-No B-C-P-No 4 PS-B-No-No PS-B-C-B PS-B-C-P 5 ES-B-C-P B-C-P-B B-C-P-B 6 No-B-C-P B-C-B-P ES-B-C-No 7 B-C-P-No ES-B-C-P PS-B-B-No 8 ES-B-C-No PS-B-C-M B-PS-C-No 9 PS-B-C-M No-B-C-P B-C-B-No 10 No-B-C-No ES-B-C-No PS-B-C-M
  16. 16. 18%
  17. 17. ~1% ELS NELSPct of STEM Majors Pct of STEM Degrees B-C-M-M B-C-M-P PS-B-PS-B PS-B-M-M B-PS-C-M PS-B-M-P B-C-B-M B-C-P-M PS-B-M-B B-C-C-P PS-B-M-M B-C-B-M B-C-C-M PS-B-M-B B-M-B-No No-B-C-M No-No-No-No B-No-C-P B-C-M-P B-C-M-No B-C-M-B PS-B-C-M ~3%
  18. 18. Analysis of “Switchers”• 60% of ss who indicated interest in STEM career in 8th grade ended up with major outside of STEM fields• 20% of ss who indicated interest in Non- STEM career ended up with STEM degree – This group accounted for roughly 80% of total number of STEM degrees• What caused these students to switch??
  19. 19. MS student interest in science (Maltese & Tai, 2011)
  20. 20. Interest in STEM jobs 35 Student e 30 n i c i 25 d e M 20 Black interest in r o Hispanic e c 15 n e i Multi c 10 STEM jobs S n i % 5 White 0 6.25 6.75 7.25 7.75 8.25 8.75 Interest in STEM jobs 40e 35n Women i Medicineci 30deM 25ro 20ecn 15 FemaleeicS 10 Maleni% 5 0 6.25 6.75 7.25 7.75 8.25 8.75 Men  Grade Timing Science
  21. 21. Impact of standardized testing (Maltese & Hochbein, 2012)• Used three cohorts of HS students in IN who participated in state testing and completed the ACT exams (N~ 4500/yr)• Tied ACT performance to school performance on state tests in English/Math during each student’s Freshman-Junior year• HLM results showed no positive association between school status and student scores
  22. 22. Graphical literacy (Harsh & Maltese, 2012)
  23. 23. Study Methods• Streams of data collected to investigate how students and scientists interpret and construct graphs Stream 1: Graph Interpretation • Web-based survey in which participants were asked to read and analyze graphical representations of data Stream 2: Assessment of cognitive processes • Eye movement measurements/tracking and think aloud recordings Stream 3: Graph Construction • Transformation of provided data into graphical representations
  24. 24. Impact of REUs/UREs (Harsh, Maltese & Tai, 2011) (Harsh, Maltese & Tai, Forthcoming)
  25. 25. What are the indicated benefits of participation in UREs? Total Population (n=3014) Item %Exposure to genuine scientific research 49Built confidence to conduct research 16Development of basic lab techniques 15Maintained interest in science 5Influenced my decision to explore other areas 4Application of principles learned in class 4Exposure to graduate students 4Exposure to research group/meetings discussions 2Development of presentation skills 1Exposure to literature 1
  26. 26. Gender Differences in Chemistry and Physics UREs• Male and female participation rates have made equivocal percentage-wise gains since the 1940s – During this period, women in chemistry and physics were more likely to participate in these programs than their male counterparts.• Similar benefits reported across genders – Female participants were more likely to select gains associated with self- efficacy and maintenance of interest.• Female participants reported that URE participation often played a formative role in the pursuit of advanced chemistry and physics degrees at a significantly higher rate than male participants.
  27. 27. Planned URE Research• Multi-site assessment of URE program variables that influence short- and long-term outcomes for students• Observational studies on the activities and practices of URE participants in the research setting• Design and implementation of a performance based measure as a means to assess the development of students’ skills through URE participation
  28. 28. Synthesis• Flat growth in STEM degrees (some decline)• Engaging students early appears to be important, seems that many students lose interest in science during early teen years• Focus on standardized testing may not be strengthening skills of college bound students• College students lack graphical literacy skills expected by science faculty• UREs seem to have positive impact, but definition of gains unclear

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