縱貫性網路使用行為對學業成就的影響：潛藏轉移模型分析取向
作者:國立東華大學師資培育中心曾明基
卷期：64卷第4期
日期：2019年12月
頁碼：31-59
DOI：10.6209/JORIES.201912_64(4).0002
摘要：
目前探究網路使用行為對學業成就的影響，僅侷限於橫斷性研究，本研究進一步於縱貫性架構下，探究持續動態變化的網路使用行為對學業成就的影響。基於上述，本研究運用屏東教育長期追蹤資料庫國小四年級至六年級學生的固定追蹤樣本，並採用潛藏轉移模型進行網路使用行為對學業成就影響的動態分析。研究發現，網路使用行為可潛在地區分成五個異質群體，且隨著年級的增加，網路使用行為的轉移機率在不同群體的動態變化有所差異。進一步納進學生性別及學業成就分析發現，性別差異影響網路使用行為，且網路使用行為的潛在異質差異在學業成就上的表現不同。針對上述結果，本研究對網路使用行為的形塑及議題發展提出相關的建議。
關鍵詞：網路使用行為、潛藏轉移模型、學業成就
《詳全文》
參考文獻：
- 王涵芸、廖益興（2016）。網路使用行為與學業成就之研究─以新竹市公立國小六年級學生為例。中華行政學報，18，75-95。doi:10.6712/JCPA.201606_(18).0004 【Wang, H.-Y., & Liao, I.-S. (2016). The correlation between internet behavior and academic achievement of the public sixth-grade students in Hsinchu City. The Journal of Chinese Public Administration, 18, 75-95. doi:10. 6712/JCPA.201606_(18).0004】
- 行政院研究發展考核委員會（2013）。6-11歲學童數位學習與數位機會調查。取自http://ws.ndc.gov.tw/001/administrator/10/relfile/0/1000/3121615281771.pdf 【Research, Development Evaluation Commission, Executive Yuan. (2013). 6-11 year old schoolchild digital learning and digital opportunity survey report. Retrieved from http://ws.ndc.gov.tw/001/administrator/10/ relfile/0/1000/3121615281771.pdf】
- 吳佩芬、周倩（2016）。國小五年級網路資源合理使用之教學設計行動研究。教育科學研究期刊，61（4），147-176。doi:10.6209/JORIES.2016.61(4).06 【Wu, P.-F., & Chou, C. (2016). Development of instructions for fair use of internet resources for fifth graders: An action research. Journal of Research in Education Sciences, 61(4), 147-176. doi:10.6209/JORIES.2016.61(4).06】
- 何惠凱（2015）。國小中年級學童網路使用行為與學習成就之相關研究（未出版碩士論文）。國立高雄師範大學，高雄市。doi:10.6817/NKNU.2013.00021 【Ho, H.-K. (2015). A study on the relations among behavior of internet using and learning achievement in middle grade of elementary school (Unpublished master’s thesis). National Kaohsiung Normal University, Kaohsiung, Taiwan. doi:10.6817/NKNU.2013.00021】
- 林俊瑩（2016）。學科補習之動態變化對學習成就族群落差的影響：以屏東縣小學生為例。教育研究與發展期刊，12（4），23-56。doi:10.3966/181665042016121204002 【Lin, C.-Y. (2016). Influence of dynamic changes in subject supplementary education on ethnic gap in learning achievement: A case of elementary school students in Pingtung County. Journal of Educational Research and Development, 12(4), 23-56. doi:10.3966/181665042016121204002】
» 展開更多
- 王涵芸、廖益興（2016）。網路使用行為與學業成就之研究─以新竹市公立國小六年級學生為例。中華行政學報，18，75-95。doi:10.6712/JCPA.201606_(18).0004 【Wang, H.-Y., & Liao, I.-S. (2016). The correlation between internet behavior and academic achievement of the public sixth-grade students in Hsinchu City. The Journal of Chinese Public Administration, 18, 75-95. doi:10. 6712/JCPA.201606_(18).0004】
- 行政院研究發展考核委員會（2013）。6-11歲學童數位學習與數位機會調查。取自http://ws.ndc.gov.tw/001/administrator/10/relfile/0/1000/3121615281771.pdf 【Research, Development Evaluation Commission, Executive Yuan. (2013). 6-11 year old schoolchild digital learning and digital opportunity survey report. Retrieved from http://ws.ndc.gov.tw/001/administrator/10/ relfile/0/1000/3121615281771.pdf】
- 吳佩芬、周倩（2016）。國小五年級網路資源合理使用之教學設計行動研究。教育科學研究期刊，61（4），147-176。doi:10.6209/JORIES.2016.61(4).06 【Wu, P.-F., & Chou, C. (2016). Development of instructions for fair use of internet resources for fifth graders: An action research. Journal of Research in Education Sciences, 61(4), 147-176. doi:10.6209/JORIES.2016.61(4).06】
- 何惠凱（2015）。國小中年級學童網路使用行為與學習成就之相關研究（未出版碩士論文）。國立高雄師範大學，高雄市。doi:10.6817/NKNU.2013.00021 【Ho, H.-K. (2015). A study on the relations among behavior of internet using and learning achievement in middle grade of elementary school (Unpublished master’s thesis). National Kaohsiung Normal University, Kaohsiung, Taiwan. doi:10.6817/NKNU.2013.00021】
- 林俊瑩（2016）。學科補習之動態變化對學習成就族群落差的影響：以屏東縣小學生為例。教育研究與發展期刊，12（4），23-56。doi:10.3966/181665042016121204002 【Lin, C.-Y. (2016). Influence of dynamic changes in subject supplementary education on ethnic gap in learning achievement: A case of elementary school students in Pingtung County. Journal of Educational Research and Development, 12(4), 23-56. doi:10.3966/181665042016121204002】
- 林獻章（2015）。國小五、六年級學生線上遊戲成癮與學業成就之相關性研究─以臺中大德國小為例（未出版碩士論文）。南華大學，嘉義縣。 【Lin, X.-Z. (2015). The correlation research on 5th-and-6th-grades students’ addiction to online games and their academic achievement: A case study of Dade Elementary School in Taichung (Unpublished master’s thesis). Nanhua University, Chiayi County, Taiwan.】
- 邱皓政（2008）。潛在類別模式：原理與技術。臺北市：五南。 【Chiou, H.-J. (2008). Latent class modeling: Principles and techniques. Taipei, Taiwan: Wu-Nan Book.】
- 邱皓政（2017）。多層次模式與縱貫資料分析：Mplus 8解析應用。臺北市：五南。 【Chiou, H.-J. (2017). Multilevel modeling and longitudinal data analysis: Applications of Mplus 8. Taipei, Taiwan: Wu-Nan Book.】
- 財團法人台灣網路資訊中心（2017）。2017年台灣寬頻網路使用調查報告。取自https://www.twnic. net.tw/download/200307/20170721e.pdf 【Taiwan Network Information Center. (2017). 2017 Taiwan broadband network usage survey report. Retrieved from https://www.twnic.net.tw/download/200307/20170721e.pdf】
- 許淑惠（2007）。國小六年級學童網路使用行為、家庭相關因素與網路成癮之研究（未出版碩士論文）。靜宜大學，臺中市。 【Hsu, S.-H. (2006). A study of the internet using behavior, family factors, and internet addiction on sixth grade elementary school student (Unpublished master’s thesis). Jingyi University, Taichung, Taiwan.】
- 許嘉芳（2009）。國小高年級學生的親子關係、網路使用行為與學業成就相關之研究（未出版碩士論文）。國立中正大學，嘉義縣。 【Hsu, C.-F. (2009). A study of the relations among parent-child relationship, internet usage and academic achievement for the fifth and sixth graders in elementary school (Unpublished master’s thesis). National Chung Cheng University, Chiayi County, Taiwan.】
- 曾明基（2013）。測量誤差對成長混合模型異質性分析的影響：蒙地卡羅模擬研究與實徵資料分析（未出版博士論文）。國立東華大學，花蓮縣。 【Tseng, M.-C. (2013). Measurement error affect the heterogeneity of the growth mixture model: Monte Carlo simulation and empirical data analysis (Unpublished doctoral dissertation). National Donghua University, Hualien, Taiwan.】
- 曾明基（2017）。進行多層次建模最小可行的樣本數建議：貝氏模擬取向。教育研究與發展期刊，13（4），1-26。doi:10.3966/181665042017121304001 【Tseng, M.-C. (2017). Sample size requirements of using multilevel models: Bayesian simulation study. Journal of Educational Research and Development, 13(4), 1-26. doi:10.3966/181665042017121304001】
- 曾明基、邱皓政、張德勝、羅寶鳳（2013）。以學生評鑑教師教學量表決定教師開課或去留可行嗎？混合IRT分析取向。教育科學研究期刊，58（1），91-116。doi:10.3966/2073753X 2013035801004 【Tseng, M.-C., Chiou, H.-J., Chang, T.-S., & Lo, P.-F. (2013). Is using a SRI to determine the fate of teachers or commencement of work suitable? A mixture IRT analysis. Journal of Research in Education Sciences, 58(1), 91-116. doi:10.3966/2073753X2013035801004】
- 黃連興、許毓華、許天維（2014）。影響學生學業成就與網路使用行為之相關研究─以桃園縣一所國小為例。臺中教育大學學報：數理科技類，28（1），1-22。 【Huang, L.-X., Hsu, Y.-H., & Hsu, T.-W. (2014). The relationship between students’ academic achievements and internet usage behaviors at an elementary school in Taoyuan County. Journal of National Taichung University of Education, 28(1), 1-22.】
- 黃瑟娟（2011）。新北市三重與蘆洲兩所國小高年級學童網路成癮與學業成就相關之研究（未出版碩士論文）。銘傳大學，臺北市。 【Huang, S.-J. (2011). A study of internet addiction and academic achievement for fifth and sixth grade students of two elementary schools at Sanchong and Luzhou in New Taipei City (Unpublished master’s thesis). Ming Chuan University, Taipei, Taiwan.】
- 楊志堅、吳齊殷（2001）。潛藏轉移模式在社會縱貫研究之應用：以青少年暴力行為發展研究為例。調查研究，9，5-33。doi:10.7014/TCYC.200104.0005 【Yang, C.-C., & Wu, C.-I. (2001). Latent transition models for longitudinal sociology study: A paradigm of adolescences deviant behavior development. Survey Research, 9, 5-33. doi:10.7014/TCYC.200104.0005】
- 楊易蕙（2005）。國小學童網路使用行為與人際關係、自我概念之研究（未出版碩士論文）。國立臺南大學，臺南市。 【Yung, Y.-H. (2005). Research among behavior of using internet and interpersonal relationship, self-concept for elementary school students (Unpublished master’s thesis). National Tainan University, Tainan, Taiwan.】
- 廖思涵（2005）。高雄市國中生網路使用行為、網路沉迷與生活適應、學業成就之相關研究（未出版碩士論文）。國立高雄師範大學，高雄市。 【Liao, S.-H. (2005). A study on the relations among behavior of internet using, internet addiction, life adjustment and learning achievement in junior high school in Kaoshiung City (Unpublished master’s thesis). National Kaohsiung Normal University, Kaohsiung, Taiwan.】
- 蔡秀英（2009）。澎湖縣國小學童涉入網路遊戲與其同儕關係、學業成就之相關研究（未出版碩士論文）。國立臺南大學，臺南市。 【Tsai, S.-Y. (2009). A study of the correlation between the involving in internet games of primary school students and peer relationship and academic performance (Unpublished master’s thesis). National Tainan University, Tainan, Taiwan.】
- 蔡政軒（2011）。高雄市國小高年級學童在校學習態度與網路成癮之相關研究（未出版碩士論文）。國立高雄師範大學，高雄市。 【Tsai, J.-S. (2011). A study on learning attitude in school and internet addiction for senior students of elementary school in Kaohsiung (Unpublished master’s thesis). National Kaohsiung Normal University, Kaohsiung, Taiwan.】
- 劉雅文（2010）。國小高年級學生網路使用行為與自我概念、學業成就之研究（未出版碩士論文）。中華大學，新竹市。 【Liu, Y.-W. (2010). A study of self-concept and learning achievement on internet user behavior for high grade students in elementary school (Unpublished master’s thesis). Chung Hua University, Hsinchu, Taiwan.】
- 鄧瑞源（2007）。新竹市國民小學高年級學生網路使用行為及其影響之研究（未出版碩士論文）。國立新竹教育大學，新竹市。 【Teng, R.-Y. (2007). Internet use behavior of high grades of elementary school students in Hsinchu City (Unpublished master’s thesis). National Hsinchu University of Education, Hsinchu, Taiwan.】
- 魏心怡（2001）。網際網路與心理幸福、學業成績（未出版碩士論文）。國立臺東師範學院，臺東市。 【Wei, H.-I. (2001). Internet and psychological well-being, academic achievement (Unpublished master’s thesis). National Taitung Teacher College, Taitung, Taiwan.】
- 嚴增虹（2002）。國小學童網際網路使用者背景、行為與心理特質關係之研究（未出版碩士論文）。國立臺南大學，臺南市。 【Yen, T.-H. (2002). Research on the relationship between background, behavior of using internet and psychological characteristics for elementary school students (Unpublished master’s thesis). National Tainan University, Tainan, Taiwan.】
- 蘇素敏（2015）。高年級學童網路成癮現象對學業成就及身心健康相關之研究（未出版碩士論文）。南華大學，嘉義縣。 【Su, S.-M. (2015). A study of internet addiction of elementary high grade students effects the academic achievement and mental health (Unpublished master’s thesis). Nanhua University, Chiayi County, Taiwan.】
- Asparouhov, T., & Muthén, B. O. (2014a). Auxiliary variables in mixture modeling: Three-step approaches using Mplus. Structural Equation Modeling: A Mutidisciplinary Journal, 21(3), 329-341. doi:10.1080/10705511. 2014.915181
- Asparouhov, T., & Muthén, B. O. (2014b). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary second model. Retrieved from http://www.statmodel.com/download/asparouhov_muthen_2014.pdf
- Bakk, Z., Tekle, F. B., & Vermunt, J. K. (2013). Estimating the association between latent class membership and external variables using bias adjusted three-step approaches. Sociological Methodology, 43(1), 272-311. doi:10.1177/0081175012470644
- Baum, L. E., Petrie, T., Soules, G., & Weiss, N. (1970). A maximization technique occurring in the statistical analysis of probabilistic function of Markov chains. Annals of Mathematical Statistics, 41(1), 164-171. doi:10.1214/aoms/1177697196
- Biagi, F., & Loi, M. (2013). Measuring ICT use and learning outcomes: Evidence from recent econometric studies. European Journal of Education, 48(1), 28-42. doi:10.1111/ejed.12016
- Boeschoten, L., Oberski, D. L., Waal, T. D., & Vermunt, J. K. (2018). Updating latent class imputations with external auxiliary variables. Structural Equation Modeling: A Multidisciplinary Journal, 25(5), 750-761. doi:10.1080/10705511.2018.1446834
- Celeux, G., & Soromenho, G. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13(2), 195-212. doi:10.1007/BF01246098
- Chang, F.-C., Chiu, C.-H., Miao, N.-F., Chen, P.-H., Lee, C.-M., Chiang, J.-T., & Pan, Y.-C. (2015). The relationship between parental mediation and Internet addiction among adolescents, and the association with cyberbullying and depression. Comprehensive Psychiatry, 57, 21-28. doi:10.1016/j.comppsych.2014.11.013
- Chen, S.-Y., & Tzeng, J.-Y. (2010). College female and male heavy internet users’ profiles of practices and their academic grades and psychosocial adjustment. Cyberpsychology Behavior and Social Networking, 13(3), 257-262. doi:10.1089/cyber.2009.0023
- Cho, S. J., Cohen, A. S., Kim, S. H., & Bottge, B. (2010). Latent transition analysis with a mixture item response theory measurement model. Applied Psychological Measurement, 34(7), 483-504. doi:10.1177/0146621610362978
- Choi, H. J., & Temple, J. R. (2016). Do gender and exposure to interparental violence moderate the stability of teen dating violence? Latent transition analysis. Prevention Science, 17(3), 367-376. doi:10.1007/s11121-015-0621-4
- Collins, L. M., & Lanza, S. T. (2009). Latent class and latent transition analysis: With applications in the social, behavioral and health sciences. Hoboken, NJ: John Wiley & Sons. doi:10.1002/ 9780470567333
- Collins, L. M., & Wugalter, S. E. (1992). Latent class models for stage-sequential dynamic latent variables. Multivariate Behavioral Research, 27(1), 131-157. doi:10.1207/s15327906mbr 2701_8
- Geng, J., Han, L., Gao, F., Jou, M., & Huang, C.-C. (2018). Internet addiction and procrastination among Chinese young adults: A moderated mediation model. Computers in Human Behavior, 84, 320-333. doi:10.1016/j.chb.2018.03.013
- Kam, C., Morin, A. J. S., Meyer, J. P., & Topolnytsky, L. (2016). Are commitment profiles stable and predictable? A latent transition analysis. Journal of Management, 42(6), 1462-1490. doi:10.1177/0149206313503010
- Kiyici, M., Kiyici, F. B., & Franklin, T. (2012). Examining freshmen believe concerning ICT usage in K-12 and university settings. Turkish Online Journal of Educational Technology, 11(4), 427-431. doi:10.1016/j.sbspro.2011.04.403
- Koukounari, A., Donnelly, C. A., Moustaki, I., Tukahebwa, E. M., Kabatereine, N. B., Wilson, S., …van Dam, G. J. (2013). A latent markov modelling approach to the evaluation of circulating cathodic antigen strips for schistosomiasis diagnosis pre- and post-praziquantel treatment in Uganda. PLoS Computational Biology, 9(12), e1003402. doi:10.1371/journal.pcbi. 1003402
- Lin, M.-P., Wu, J.-Y. W., You, J., Hu, W.-H., & Yen, C.-F. (2018). Prevalence of internet addiction and its risk and protective factors in a representative sample of senior high school students in Taiwan. Journal of Adolescence, 62, 38-46. doi:10.1016/j.adolescence.2017.11.004
- Luu, K., & Freeman, J. G. (2011). An analysis of the relationship between information and communication technology (ICT) and scientific literacy in Canada and Australia. Computers & Education, 56(4), 1072-1082. doi:10.1016/j.compedu.2010.11.008
- Machin, S., McNally, S., & Silva, O. (2007). New technology in schools: Is there a payoff? The Economic Journal, 117(522), 1145-1167. doi:10.1111/j.1468-0297.2007.02070.x
- Meeus, W., van de Schoot, R., Klimstra, T., & Branje, S. (2011). Personality types in adolescence: Change and stability and links with adjustment and relationships: A five-wave longitudinal study. Developmental Psychology, 47(4), 1181-1195. doi:10.1037/a0023816
- Mullis, I. V. S., Martin, M. O., Foy, P., & Arora, A. (2012). TIMSS 2011 international results in mathematics. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College.
- Mullis, I. V. S., Martin, M. O., Foy, P., & Drucker, K. T. (2012). PIRLS 2011 international results in reading. Chestnut Hill, MA: TIMSS & PIRLS International Study Center, Lynch School of Education, Boston College.
- Muthén, B. O. (2001a). Latent variable mixture modeling. In G. A. Marcoulides & R. E. Schumacker (Eds.), New developments and techniques in structural equation modeling (pp. 1-33). Mahwah, NJ: Lawrence Erlbaum Associates.
- Muthén, B. O. (2001b). Second-generation structural equation modeling with a combination of categorical and continuous latent variables: New opportunities for latent class/latent growth modeling. In L. M. Collins & A. Sayer (Eds.), New methods for the analysis of change (pp. 291-322). Washington, DC: American Psychological Association.
- Muthén, B. O. (2002). Beyond SEM: General latent variable modeling. Behaviormetrika, 29(1), 81-117. doi:10.2333/bhmk.29.81
- Muthén, B. O. (2008). Latent variable hybrids: Overview of old and new models. In G. R. Hancock & K. M. Samuelsen (Eds.), Advances in latent variable mixture models (pp. 1-24). Charlotte, NC: Information Age. doi:10.1080/10705511003661595
- Muthén, B. O., & Asparouhov, T. (2011). LTA in Mplus: Transition probabilities influenced by covariates. Retrieved from http://www.statmodel.com/examples/LTAwebnote.pdf
- Muthén, L. K., & Muthén, B. O. (1998-2012). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.
- Papanastasiou, E. C., Zembylas, M., & Vrasidas, C. (2003). Can computer use hurt science achievement? The USA results from PISA. Journal of Science Education and Technology, 12(3), 325-332. doi:10.1023/A:1025093225753
- Park, J., & Yu, H.-T. (2018). A comparison of approaches for estimating covariate effects in nonparametric multilevel latent class models. Structural Equation Modeling: A Multidisciplinary Journal, 25(5), 778-790. doi:10.1080/10705511.2018.1448711
- Spiezia, V. (2010). Does computer use increase educational achievements? Student-level evidence from PISA. OECD Journal: Economic Studies, 1, 1-22. doi:10.1787/eco_studies-2010-5km33 scwlvkf
- Tsai, M.-J., & Tsai, C.-C. (2010). Junior high school students internet usage and self-efficacy: A re-examination of the gender gap. Computers & Education, 54(4), 1182-1192. doi:10.1016/j. compedu.2009.11.004
- Vermunt, J. K. (2010). Latent class modeling with covariates: Two improved three-step approaches. Political Analysis, 18(4), 450-469. doi:10.1093/pan/mpq025
- Vermunt, J. K., Langeheine, R., & Böckenholt, U. (1999). Discrete-time discrete-state latent Markov models with time-constant and time varying-covariates. Journal of Educational and Behavioral Statistics, 24(2), 179-207. doi:10.3102/10769986024002179
- Wainer, J., Dwyer, T., Dutra, R. S., Covic, A., Magalhaes, V. B., Ferreira, L. R. R., …Claudio, K. (2008). Too much computer and internet use is bad for your grades, especially if you are young and poor: Results from the 2001 Brazilian SAEB. Computers & Education, 51(4), 1417-1429. doi:10.1016/j.compedu.2007.12.007
- Wiggins, L. M. (1973). Panel analysis. Amsterdam, NL: Elsevier.
- Wittwer, J., & Senkbeil, M. (2008). Is students’ computer use at home related to their mathematical performance at school? Computers & Education, 50(4), 1558-1571. doi:10.1016/j.compedu. 2007.03.001
Journal directory listing - Volume 64 (2019) - Journal of Research in Education Sciences【64(4)】December
The Effect of the Internet Use Behavior on Academic Achievement: Latent Transition Model Analysis
Author: Ming-Chi Tseng (Center for Teacher Education, National Dong Hwa University)
Vol.&No.：Vol. 64, No.4
Date：December 2019
Pages：31-59
DOI：10.6209/JORIES.201912_64(4).0002
Abstract：
The literature on the effect of Internet use behavior on academic achievement has been limited to cross-sectional studies, but this study adopted a longitudinal framework and used the latent transition model to analyze data from the Pingtung Education Longitudinal Survey database. The study found that Internet use behavior can be divided into five heterogeneous groups, and as the grade increases, the transfer rate of Internet use behavior varies among the groups. Further analysis revealed that gender differences influence Internet use behavior, and that the potential heterogeneity of Internet use behaviors depends on academic achievement. This study proposes suggestions relevant to Internet use behavior and development.
Keywords：academic achievement, Internet use behavior, latent transition model