CoChat
Sign Up
Cited by 79

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

Is Science Me? Exploring Middle School Students’ STE-M Career Aspirations

Aschbacher, Pamela R., Ing, Marsha, Tsai, Sherry M.·2014·Journal of Science Education and Technology
DOI 10.1007/s10956-014-9504-x
Open this paper in CoChat — free account

Overview

Integrity signals

Registry

Crossref · 10.1007/s10956-014-9504-x

Cites

6 of 6 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Research works printed but not linked: 51

  1. Archer L, DeWitt J, Osborne J, Dillon J, Willis B, Wong B (2012) Science aspirations, capital, and family habitus: how families shape children’s engagement and identification with science. Am Educ Res J 49(5):881–908 · DOI
  2. Aschbach PR, Ing M, Tsai S (2013) Boosting student interest in science. Phi Delta Kappan 95(2):47–51 · DOI
  3. Aschbacher PR, Li E, Roth EJ (2010) Is science me? high school students’ identities, participation and aspirations in science, engineering, and medicine. J Res Sci Teach 47(5):564–582 · DOI · Paper page
  4. Asparouhov T, Muthén BO (2012) Using Mplus TECH11 and TECH14 to test the number of latent classes (Mplus web notes: no. 14). Mplus, Los Angeles
  5. Atwater MM, Wiggins J, Gardner CM (1995) A study of urban middle school student with high and low attitudes toward science. J Res Sci Teach 32(6):665–677 · DOI
  6. Baker D, Leary R (1995) Letting girls speak out about science. J Res Sci Teach 32:3–27 · DOI
  7. Bakk Z, Oberski DL, Vermunt JK (2014) Relating latent class assignments to external variables: standard errors for correct inference. Polit Anal. doi: 10.1093/pan/mpu003 · DOI
  8. Bartholomew DJ (1987) Latent variable models and factor analysis. Oxford University Press, New York
  9. Brickhouse NW, Lowery P, Schultz K (2000) What kind of girl does science? The construction of school science identities. J Res Sci Teach 37(5):441–458 · DOI
  10. Calabrese Barton A, Kang H, Tan E, O’Neill TB, Bautista-Guerra J, Caitlin B (2013) Crafting a future in science: tracing middle school girls’ identity work over time and space. Am Educ Res J 50:3–75 · DOI
  11. Carlone HB (2003) Innovative science within and against a culture of “achievement”. Sci Educ 87(3):307–328 · DOI
  12. Catsambis S (1995) Gender, race, ethnicity and science education in the middle grades. J Res Sci Teach 32(3):243–257 · DOI
  13. Collins LM, Lanza ST (2010) Latent class and latent transition analysis: with applications in the social, behavioral, and health sciences. Wiley, New York
  14. Committee on Science, Engineering, and Public Policy (2007) Rising above the gathering storm: Energizing and employing America for a brighter economic future. The National Academies Press, Washington, DC
  15. Dewitt J, Archer L, Osborne J, Dillon J, Willis B, Wong B (2010) High aspirations but low progression: the science aspirations–careers paradox amongst minority ethnic students. Int J Sci Math Educ 9(2):243–271 · DOI
  16. Eccles JS (1984) Sex differences in achievement patterns. In: Sonderegger T (ed) Nebraska symposium on motivation, vol 32. University of Nebraska Press, Lincoln, pp 97–132
  17. Eccles JS, Harold RD (1991) Gender differences in sport involvement: applying the Eccles’ expectancy-value model. J Appl Sport Psychol 3:7–35 · DOI
  18. Eccles JS, Wigfield A (1995) In the mind of the achiever: the structure of adolescents’ academic achievement related-beliefs and self-perceptions. Pers Soc Psychol Bull 21:215–225 · DOI · Paper page
  19. Eccles JS, Adler TF, Futterman R, Goff SB, Kaczala CM, Meece JL, Midgley C (1983) Expectancies, values, and academic behaviors. In: Spence JT (ed) Achievement and achievement motivation. W. H. Freeman, San Francisco, pp 74–146
  20. Eccles JS, Wigfield A, Flanagan C, Miller C, Reuman D, Yee D (1989) Self-concepts, domain values and self-esteem: relations and changes in early adolescence. J Pers 57(2):283–310 · DOI
  21. Furman M, Calabrese Barton A (2006) Capturing urban student voices in the creation of a science mini-documentary. J Res Sci Teach 43(7):667–694 · DOI
  22. Gilmartin SK, Li E, Aschbacher P (2006) The relationship between interest in physical science/engineering, science class experiences, and family contexts: variations by gender and race/ethnicity among secondary students. J Women Minor Sci and Eng 12(2–3):179–207 · DOI
  23. Goodman LA (1974) Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika 61:215–231 · DOI
  24. Hagenaars JA, McCutcheon AL (eds) (2002) Applied latent class analysis. Cambridge University Press, Cambridge
  25. Hanson SL (1996) Lost talent: women in the sciences. Temple University Press, Philadelphia
  26. Heinen T (1996) Latent class and discrete latent trait models: similarities and differences. Sage, Thousand Oaks
  27. Kiran D, Sungur S (2012) Middle school students’ science self-efficacy and its sources: examination of gender difference. J Sci Educ Technol 21(5):619–630 · DOI
  28. Kisiel JF (2003) Teachers, museums, and worksheets: a closer look at a learning experience. J Sci Teach Educ 14:3–21 · DOI
  29. Lazarsfeld PF, Henry NW (1968) Latent structure analysis. Houghton Mifflin, New York
  30. Maltese AV, Tai RH (2010) Eyeballs in the fridge: sources of early interest in science. Int J Sci Educ 32(5):669–685 · DOI
  31. Masnick AM, Valenti SS, Cox BD, Osman CJ (2010) A multidimensional scaling analysis of students’ attitudes about science careers. Int J Sci Educ 32(5):653–667 · DOI
  32. Masyn K (2013) Latent class analysis and finite mixture modeling. In: Little T (ed) The Oxford handbook of quantitative methods in psychology, vol 2. Oxford University Press, Oxford, pp 375–393
  33. McCoach DB, Siegle D (2003) The school attitude assessment survey-revised: a new instrument to identify academically able students who underachieve. Educ Psychol Meas 63(3):414–429 · DOI
  34. Muthén BO (1992) Latent variable modeling in epidemiology. Alcohol Health Res World 16:286–292
  35. Muthén BO (2001) Latent variable mixture modeling. In: Marcoulides GA, Schumacker RE (eds) New development and techniques in structural equation modeling. Lawrence Erlbaum Associates, Mahwah, pp 1–33
  36. NGSS Lead States (2013) Next generation science standards: for states, by states. National Academies Press, Washington, DC
  37. Oakes J (1990) Opportunities, achievement, and choice: women and minority students in science and mathematics. Rev Res Educ 16:153–222
  38. Osborne J, Simon S, Collins S (2003) Attitudes towards science: a review of the literature and its implications. Int J Sci Educ 25(9):1049–1079 · DOI
  39. Raved L, Zvi Assaraf OB (2011) Attitudes toward science learning among 10th grade students: a qualitative look. Int J Sci Educ 33(9):1219–1243 · DOI
  40. Sadker M, Sadker D, Klein S (1991) The issue of gender in elementary and secondary education. Rev Res Educ 17:269–334
  41. Schwartz G (1978) Estimating the dimensions of a model. Ann Stat 6(2):461–464 · DOI · Paper page
  42. Simpson RD, Oliver JS (1990) A summary of major influences on attitude toward and achievement in science among adolescent students. Sci Educ 74:1–18 · DOI
  43. StataCorp (2009) Stata statistical software (release 11). StataCorp LP, College Station
  44. Tai RH, Liu CQ, Maltese AV, Fan X (2006) Planning early for careers in science. Science 312(5777):1143–1144 · DOI
  45. Tan E, Calabrese Barton A (2008) Unpacking science for all through the lens of identities-in-practice: the stories of Amelia and Ginny. Cult Sci Educ 3(1):43–71 · DOI
  46. Vermunt JK (2010) Latent class modeling with covariates: two improved three-step approaches. Polit Anal 18:450–469 · DOI
  47. Vuong Q (1989) Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica 57:307–333 · DOI · Paper page
  48. Wigfield A, Eccles J (2000) Expectancy-value theory of achievement motivation. Contemp Educ Psychol 25:68–81 · DOI · Paper page
  49. Wigfield A, Eccles J, Mac Iver D, Reuman D, Midgley C (1991) Transitions at early adolescence: changes in children’s domain-specific self-perceptions and general self-esteem across the transition to junior high school. Dev Psychol 27(4):552–565 · DOI · Paper page
  50. Wigfield A, Eccles JS, Yoon KS, Harold RD, Arbreton A, Freedman-Doan K, Blumenfeld PC (1997) Changes in children’s competence beliefs and subjective task values across the elementary school years: a three year study. J Educ Psychol 89(3):451–469 · DOI
  51. Xu J, Coats LT, Davidson ML (2012) Promoting student interest in science: the perspective of exemplary African American teachers. Am Educ Res J 49:124–154 · DOI

Cited by

Sorted by citations

See all 79

Metadata

Authors
Aschbacher, P. R., Ing, M., & Tsai, S. M.
Venue
Journal of Science Education and Technology
Publisher
Springer Science and Business Media LLC
Published
2014-07-06
Volume
23
Issue
6
Pages
735-743
ISSN
  • 1059-0145
  • 1573-1839
DOI
10.1007/s10956-014-9504-x
Cited by
79
References
6
Language
en
Licence
www.springer.com/tdm (tdm)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review