台灣的高中職與五專的分流制度，高中通常於高二進行類組選擇，高職與五專則是在入學前就必須選擇學習領域。升大學時，學生多以「成績」來決定其志願序，而非對學習領域的興趣作為優先順序的考量，大學科系主修領域的選擇，應該只是高中類組的延伸，因此探討高中至大學學習領域的持續性是有其必要性。
	國外文獻在探討學習領域持續性的研究已累積一些成果，但國內的討論仍是鮮少。因此，本文利用「臺灣青少年成長歷程研究」 (Taiwan Youth Project, TYP) 的長期追蹤樣本資料，探討普通學程學生，從高中到大學端，影響學習領域持續性的因素，藉此補足國內文獻不足之處。本文將學習領域持續性定義為：大學科系領域與高中類組相同者，則具有學習領域持續性；反之，大學科系領域與高中類組相異者，則不具有學習領域持續性。
	另外，本文亦使用高中組別 (社會組和自然組)，以及男女性別，將樣本區別為：社會組、自然組、男生、女生、社會組男生、社會組女生、自然組男生和自然組女生，依序分別檢視影響學習領域持續性的因素。控制變數包括學生個人特性、家庭背景、學校因素、高中補習情況和15歲居住地區。
	實證結果顯示，在全部樣本分析中，自我評價、家庭月收入及父母性別角色態度，皆對學習領域持續性有負向影響。在子樣本分析當中，社會組分析顯示，性別、自我評價、比賽參與、家庭月收入和補習科目，皆會降低學習領域持續性；自然組分析發現，班級排名、自己對學業表現滿意程度與15歲居住地區，皆會增加自然組學習領域持續性，另一方面，家庭月收入和補文科，則會降低自然組學習領域持續性。在男生樣本中，班級排名、自我評價和補習科目，對學習領域持續性有顯著影響。另外，在女生樣本中，比賽參與、家庭月收入、父母性別角色態度、補習科目和15歲居住地區，對學習領域持續性有顯著影響。此外，在社會組男生和女生分析部分，班級排名、自我評價、比賽參與、家中老大以及父母性別角色態度，皆對社會組男生學習領域持續性有顯著影響；家庭月收入與補習科目，皆對社會組女生的學習領域持續性有顯著影響。在自然組男生和女生的結果發現，班級排名、比賽參與、家庭月收入、補習變數以及15歲居住地區，對自然組男生學習領域持續性有顯著影響；家庭月收入以及對班級老師不滿意對自然組女生學習領域持續性有顯著關係。
總結而言，性別對於社會組和自然組學習領域持續性有不同方向的影響，在社會組當中，相較於女生，男生較容易轉換學習領域；在自然組當中，則是女生較容易轉換學習領域。換言之，除了女生在理工領域存在管漏現象之外，男生在人文社會領域亦有相似的管漏現象。另外，本文得出三點發現：首先，影響學習領域持續性的因素並不一定只有被單一面向因素所影響，如個人特性或家庭背景；第二，父母的性別角色態度可能會影響「男理工、女人文」的差異；第三，補習科目和比賽類型，似乎在某種程度上顯現學生對學習領域的偏好，故此高中類組可能不會是學生選擇大學科系時唯一的考量。

Due to the tracking system in high schools and junior college in Taiwan, high school students choose their study program to concentrate on when they are second grader. While junior college students and vocational high school students have to choose their field of study before enrolling. When the students apply for universities and majors, they mostly use grades rather than interests. A student’s choice of major should be seemed as an extension of the high school program which they have chosen. Therefore, it is essential to discuss on the persistence in the field of study from high school to university.
Some results have been accumulated in foreign studies on the persistence in the field of study；however, domestic studies on this issue are still rare. To make up for the lack of domestic literature, this study uses the panel data of the Taiwan Youth Project (TYP) to explore the factors that would affect the persistence in students’ field of study. The persistence in the field of study is defined that the college student whose field of study does not change from high school to university, on the contrary, the college student whose field of study does change from high school to university means that the student doesn’t have persistence in the field of study.
This study also conducts a series of sub-sample analyses according to genders and fields of study: social program and science program, men and women, both gender in the social program as well as in science program. The control variables include the students’ characteristics, family background, school factors, high-school tutoring situation, and 15-year-old residential area.
The empirical results show that self-evaluation, monthly family income, and the parent’s attitude toward different gender roles all show negative effects in the total student sample. In the sub-sample analysis, the social program analysis showed gender, self-evaluation, competition participation, monthly family income and tuition subjects have a negative relationship in society program；on the other hands, class ranking, degree of satisfaction with academic performance and 15-year-old living area showed a positive relationship in the science program. On the contrary, monthly family income and studying liberal arts subjects showed a negative relationship in the science program. Among the men sample, class ranking, self-evaluation, and tutoring subjects have a significant impact on persistence in the field of study. While the women sample, competition participation, monthly family income, gender roles of parents, tutoring subjects, and 15-year-old residential area have a significant effect on their persistence. As for men in the social program, class ranking, self-evaluation, competition participation, the eldest child, and gender roles of parents all have a significant effect on social program persistence. Additionally, monthly family income and tutoring subjects have a significant relationship for women in the social program. Also, men in the science program, class ranking, competition participation, monthly family income, tutoring subjects, and 15-year-old residential area have a significant effect. For women in the science program, monthly family income and dissatisfaction with class teachers have a significant relationship.
In summary, gender has opposite effects on the persistence of the fields of study in social program and science program. Among the social program, compared to women, men are more likely to switch the fields of study；in the science program, women are more likely to switch the fields of study. Namely, not only do women become underrepresented minorities in the science fields, which presents a phenomenon called leaky pipeline, but also men have a similar situation in liberal art majors. Besides, this study draws three findings: First, the persistence in the field of study may be affected by students’ characteristics, family background or school factors. Secondly, parent’s attitudes toward gender roles may affect the likelihood that men choose to study in science-related majors and the likelihood that women choose to study in liberal art-related majors. Third, the tutoring subjects and participating in competitions and contests during high school may also affect the likelihood of the persistence of the study field.

目錄
1 前言	1
2 文獻回顧	3
2.1學習持續性的討論	3
2.2影響就學持續性的因素	4
2.2.1個人特性	5
2.2.2 家庭特性	6
2.2.3 學校特性	6
2.3高中選組的決定因素	7
2.4影響STEM學習領域持續性之因素	8
3 資料	12
3.1資料來源	12
3.2變數定義	13
3.3變數敘述統計量	17
4實證迴歸結果	22
4.1 實證策略	22
4.2學習領域持續性的決定因素	23
4.3依類組分類之學習領域樣本持續性分析	25
4.3.1社會組學習領域持續性的決定因素	25
4.3.2自然組學習領域持續性的決定因素	27
4.4依類組和性別分類之學習領域持續性分析	29
5 結論	33
參考文獻	36

表目錄
表1：高中類組與大學主修領域	43
表2：性別與高中類組	43
表3：性別與大學主修領域	43
表4：學習領域持續性的性別差異	43
表5：人文社會學習領域持續性的性別差異	44
表6：理工醫農學習領域持續性的性別差異	44
表7：相關變數敘述統計量	45
表8：學習領域持續性的決定因素	46
表9：社會組學習領域持續性的決定因素	48
表10：自然組學習領域持續性的決定因素	50
表11：學習領域持續性的決定因素--依高中類組和性別分	52

參考文獻
中文部分
陳婉琪 (2013)。高中生選組行為的原因與結果：性別、信念、教師角色與能力
	發展。台灣社會學期刊，(25)，89-123。
教育部統計處 (2008)。大專校院學生休、退學概況及就學穩定情形。
取自https://stats.moe.gov.tw
郭祐誠、許聖章 (2011)。數學能力與性別對高中學生選組之影響。經濟
	論文叢刊，39(4)，541-591。
楊巧玲 (2005)。性別化的興趣與能力：高中學生類組選擇之探究。台灣教
育社會學研究，5(2)，113-153。
楊龍立 (1993)。我國高中學生主修科別與性別的關係之研究，教育研究資
	訊，1(3)，64-75。
劉正、陳建州 (2007)。臺灣高等教育學習領域之性別區隔與變遷：1972-
	2003。 教育心理學期刊，30(4)，1-25.。
盧雪梅、毛國楠 (2008)。國中基本學力測驗數學科之性別差異與差別試題功能 
	(DIF) 分析。教育實踐與研究，21(2)，95-126。
謝小芩、林大森與陳佩英 (2011)。性別科系跨界?大學生的性別與科系選擇。
	台灣社會學刊，48，95-149。
謝小芩 (2017)。從量變邁向質變-科技領域的性別研究。性別平等教育季
	刊，(80)，52-59。
英文部分
Allen, J., & Robbins, S. B. (2008). Prediction of college major persistence based on 
vocational interests, academic preparation, and first-year academic performance. Research in Higher Education, 49(1), 62-79.
Astin, H. S., & Sax, L. J. (1996). Developing scientific talent in undergraduate 
women. The equity equation: Fostering the advancement of women in the sciences,mathematics, and engineering, 96-121.
Astin, A. W. (1997). How “good” is your institution's retention rate?. Research in 
higher education, 38(6), 647-658.
Bean, J. P. (1980). Dropouts and turnover: The synthesis and test of a causal model of 
student attrition. Research in higher education, 12(2), 155-187.
Burtner, J. (2005). The use of discriminant analysis to investigate the influence of 
	non‐cognitive factors on engineering school persistence. Journal of Engineering 
	Education, 94(3), 335-338.
Brainard, S. G., & Carlin, L. (1998). A six‐year longitudinal study of undergraduate 
women in engineering and science. Journal of Engineering Education, 87(4), 369-375.
Bank, B. J., Slavings, R. L., & Biddle, B. J. (1990). Effects of peer, faculty, and
parental influences on students' persistence. Sociology of education, 208-225.
Clark Blickenstaff, Jacob. Women and science careers: leaky pipeline or gender
filter?. Gender and education, 2005, 17.4: 369-386.
Christensen, P. M. (1990). A comparison of adult baccalaureate graduates and
nonpersisters. University of Minnesota.
Choy, S. P. (2001). Students whose parents did not go to college: Postsecondary 
	access, persistence, and attainment.
Canaan, S., & Mouganie, P. (2021). The Impact of Advisor Gender on Female 
	Students’ STEM Enrollment and Persistence. Journal of Human Resources, 0320-
	10796R2.
Dweck, C. S. (1986). Motivational processes affecting learning. American 
	psychologist, 41(10), 1040.
Eccles, J. S., Barber, B., & Jozefowicz, D. (1999). Linking gender to educational, 
occupational, and recreational choices: Applying the Eccles et al. model of 
achievement-related choices.
Erwin, L. & Maurutto, P. (1998) Beyond access: considering gender deficits in 
science education,Gender and Education, 10(1), 51–69..
Fike, D. S., & Fike, R. (2008). Predictors of first-year student retention in the 
community college. Community college review, 36(2), 68-88.
Graham, M. J., Frederick, J., Byars-Winston, A., Hunter, A. B., & Handelsman, J. 
(2013). Increasing persistence of college students in STEM. Science, 341(6153), 
1455-1456.
Good, C., Aronson, J., & Inzlicht, M. (2003). Improving adolescents' standardized test 
performance: An intervention to reduce the effects of stereotype threat. Journal 
of Applied Developmental Psychology, 24(6), 645-662.
Greenwald, A. G., Banaji, M. R., Rudman, L. A., Farnham, S. D., Nosek, B. A., & 
Mellott, D. S. (2002). A unified theory of implicit attitudes, stereotypes, self-
esteem, and self-concept. Psychological review, 109(1), 3.
Gansemer-Topf, A. M., Kollasch, A., & Sun, J. (2017). A house divided? Examining 
	persistence for on-campus STEM and non-STEM students. Journal of College 
	Student Retention: Research, Theory & Practice, 19(2), 199-223.
Hyde, M. S., & Gess-Newsome, J. (2000). Factors that increase persistence of female 
	undergraduate science students. Women succeeding in the sciences: Theories and 
	practices across disciplines, 115-137.
Henes, R. (1994). Creating gender equity in your teaching. College of Engineering, 
	University of California, Davis.
Horn, L., & Nuñez, A. M. (2000). Mapping the road to college first-generation
 students' math track, planning strategies, and context of support. Diane
 Publishing.
Ivie, R., Czujko, R., & Stowe, K. (2002, September). Women physicists speak: The 
	2001 international study of women in physics. In AIP Conference Proceedings 
	(Vol. 628, No. 1, pp. 49-70). American Institute of Physics.
Kinzie, J., Thomas, A. D., Palmer, M. M., Umbach, P. D., & Kuh, G. D. (2007). 
Women students at coeducational and women's colleges: How do their 
experiences compare?. Journal of College Student Development, 48(2), 145-165.
King, B. (2016). Does postsecondary persistence in STEM vary by gender?. Aera 
	Open, 2(4), 2332858416669709.
Kim, K., Fann, A., & Misa-Escalante, K. (2009). Engaging women in computer 
	science and engineering: Insights from a national study of undergraduate
	research experiences.
Kuh, G. D., Cruce, T. M., Shoup, R., Kinzie, J., & Gonyea, R. M. (2008). Unmasking 
the effects of student engagement on first-year college grades and persistence. 
The journal of higher education, 79(5), 540-563.
Koenig, K., Schen, M., Edwards, M., & Bao, L. (2012). Addressing STEM Retention 	Through a Scientific Thought and Methods Course. Journal of College Science 
	Teaching, 41(4).
Legewie, J., & DiPrete, T. A. (2014). Pathways to science and engineering bachelor's 
	degrees for men and women. Sociological Science, 1, 41-48.
Miller, K., Sonnert, G., & Sadler, P. (2018). The influence of students’ participation in 
	STEM competitions on their interest in STEM careers. International Journal of 
	Science Education, Part B, 8(2), 95-114.
Murtaugh, P. A., Burns, L. D., & Schuster, J. (1999). Predicting the retention of 
university students. Research in higher education, 40(3), 355-371.
Margolis, J., Fisher, A., & Miller, F. (2000). The anatomy of interest: Women in 
	undergraduate computer science. Women's Studies Quarterly, 28(1/2), 104-127.
Nagda, B. A., Gregerman, S. R., Jonides, J., Von Hippel, W., & Lerner, J. S. (1998). 
Undergraduate student-faculty research partnerships affect studen retention. The 
Review of Higher Education, 22(1), 55-72.
Olbrecht, A. M., Romano, C., & Teigen, J. (2016). How Money Helps Keep Students 
	in College: The Relationship between Family Finances, Merit-Based Aid, and 
	Retention in Higher Education. Journal of Student Financial Aid, 46(1), 2.
Pascarella, E. T., & Terenzini, P. T. (1979). Interaction effects in Spady and Tinto's 
	conceptual models of college attrition. Sociology of education, 197-210.
Pascarella, E. T., & Terenzini, P. T. (2005). How College Affects Students: A Third 
Decade of Research. Volume 2. Jossey-Bass, An Imprint of Wiley. 10475 
Crosspoint Blvd, Indianapolis, IN 46256.
Robertson, D. L. (1991). Gender differences in the academic progress of adult 
undergraduates: Patterns and policy implications. Journal of College Student Development.
Riegle-Crumb, C., King, B., & Irizarry, Y. (2019). Does STEM stand out? Examining 
	racial/ethnic gaps in persistence across postsecondary fields. Educational 
	Researcher, 48(3), 133-144.
Roscigno, V. J., & Ainsworth-Darnell, J. W. (1999). Race, cultural capital, and 
 educational resources: Persistent inequalities and achievement returns. Sociology of 
 education, 158-178
Roscigno, V. J., Vélez, M. B., & Ainsworth-Darnell, J. W. (2001). Language minority 
	achievement, family inequality, and the impact of bilingual education. Race and 
	Society, 4(1), 69-88.
Stewart, S., Lim, D. H., & Kim, J. (2015). Factors influencing college persistence for 
	first-time students. Journal of Developmental Education, 12-20.
Sciarra, D. T., Seirup, H. J., & Sposato, E. (2016). High School Predictors of College 
	Persistence: The Significance of Engagement and Teacher
	Interaction. Professional Counselor, 6(2), 189-202.
Strenta, A. C., Elliott, R., Adair, R., Matier, M., & Scott, J. (1994). Choosing and 
	leaving science in highly selective institutions. Research in higher 
	education, 35(5), 513-547.
Strom, R. E., & Savage, M. W. (2014). Assessing the relationships between perceived 
support from close others, goal commitment, and persistence decisions at the 
college level. Journal of College Student Development, 55(6), 531-547.
Spady, W. G. (1970). Dropouts from higher education: An interdisciplinary review 
	and synthesis. Interchange, 1(1), 64-85.
Shin, J. E. L., Levy, S. R., & London, B. (2016). Effects of role model exposure on 
	STEM and non‐STEM student engagement. Journal of Applied Social 
	Psychology, 46(7), 410-427.
Tinto, V. (1993). Building community. Liberal Education, 79(4), 16-21.
Torres, J. B., & Solberg, V. S. (2001). Role of self-efficacy, stress, social integration, 
	and family support in Latino college student persistence and health. Journal of 
	vocational behavior, 59(1), 53-63.
Takruri-Rizk, H., Jensen, K., & Booth, K. (2008). Gendered learning experience of 
	engineering and technology students. ACM SIGCAS Computers and 
	Society, 38(1), 40-52.
Witkow, M. R., Huynh, V., & Fuligni, A. J. (2015). Understanding differences in 
	college persistence: A longitudinal examination of financial circumstances, 
	family obligations, and discrimination in an ethnically diverse sample. Applied 
	developmental science, 19(1), 4-18.
Walton, J. T. (1992). The effect of input variables on the academic persistence of adult 
	students enrolled in business programs in a vocational centre. College Student 
	Journal.
Whalen, D. F., & Shelley, M. C. (2010). Academic success for STEM and non-STEM 
	majors. Journal of STEM Education: Innovations and research, 11(1).
Walsh, K. J., & Robinson Kurpius, S. E. (2016). Parental, residential, and self-belief 
	factors influencing academic persistence decisions of college freshmen. Journal 
	of College Student Retention: Research, Theory & Practice, 18(1), 49-67.
Wyer, M. (2003). Intending to stay: Images of scientists, attitudes toward women, and 
	gender as influences on persistence among science and engineering majors. 
	Journal of Women and Minorities in Science and Engineering, 9(1).
Xu, Y. J. (2016). Attention to retention: Exploring and addressing the needs of college 
	students in STEM majors. Journal of Education and Training Studies, 4(2), 67-
	76.