Skip to main content
Registrieren
Springer Professional
SUCHE
MENÜ 1 2 3 4
nach oben

Tipp

Weitere Artikel dieser Ausgabe durch Wischen aufrufen

Erschienen in: Journal of Computers in Education 4/2020

25.04.2020

From organization to elaboration: relationships between university students’ online information searching experience and judgements

verfasst von: Chiu-Lin Lai

Erschienen in: Journal of Computers in Education | Ausgabe 4/2020

Einloggen, um Zugang zu erhalten
share
TEILEN

Abstract

Previous studies have shown the effectiveness of students’ Internet self-efficacy, and identified its relationship with their academic learning performance. In addition, researchers have indicated the importance of investigating students’ cognitive and metacognitive performance in their online learning, especially in their online information searching experience and information judgements. In this study, the exploration of students’ online information searching experience and information judgements was conducted. Two instruments were adopted; one is related to online information searching experience, and the other is about online information judgements. The survey was responded to by 583 volunteer university students. There were five factors included in the online information searching experience survey, that is, information searching, source organization, online communication, metacognition, and academic self-efficacy; six factors including multiple sources, authority, content, interactive interface, elaboration, and matching were classified in the information judgements survey. The structural equation model results showed that students would take into account both sophisticated (e.g., multiple source and content) and simple information evaluation standards (e.g., authority and interactive interface) when searching for information on the Internet. On the other hand, the students’ source organizing experience and content evaluation standard are positively correlated to their searching strategy: elaboration. However, the result also found some less sophisticated behaviors, that is, a positive correlation between online communication and the searching strategy, matching. The findings of this study provide a good reference for university teachers who intend to conduct information searching activities in their courses.
Nächster Artikel Students’ performance in blended learning: disciplinary difference and instructional design factors

Sie möchten Zugang zu diesem Inhalt erhalten? Dann informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 69.000 Bücher
  • über 500 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt 90 Tage mit der neuen Mini-Lizenz testen!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 50.000 Bücher
  • über 380 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe



 


Jetzt 90 Tage mit der neuen Mini-Lizenz testen!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 58.000 Bücher
  • über 300 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko





Jetzt 90 Tage mit der neuen Mini-Lizenz testen!

Jetzt informieren
Literatur
Artino, A. R. (2010). Online or face-to-face learning? Exploring the personal factors that predict students' choice of instructional format. The Internet and Higher Education, 13(4), 272–276.
Bandura, A. (1997). Self-efficacy: The exercise of control. New York: Worth Publishers.
Bandura, A. (2009). Cultivate self-efficacy for personal and organizational effectiveness. In E. A. Locke (Ed.), Handbook of principles of organization behavior (2nd ed., pp. 179–200). New York: Wiley.
Bollen, K. A. (1989). Structural equations with latent variables. New York: Wiley.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Sage Focus Editions, 154, 136–136.
Chandra, V., & Watters, J. J. (2012). Re-thinking physics teaching with web-based learning. Computers & Education, 58(1), 631–640.
Chang, C. S., Liu, E. Z. F., Sung, H. Y., Lin, C. H., Chen, N. S., & Cheng, S. S. (2014). Effects of online college student's Internet self-efficacy on learning motivation and performance. Innovations in Education and Teaching International, 51(4), 366–377.
Chau, P. Y. K. (1997). Reexamining a model for evaluating information center success using a structural equation modeling approach. Decision Sciences, 28(2), 309–334.
Cheng, K. H., Liang, J. C., & Tsai, C. C. (2013). University students’ online academic help seeking: The role of self-regulation and information commitments. The Internet and Higher Education, 16, 70–77.
Cheng, Y. H., & Tsai, C. C. (2017). Online research behaviors of engineering graduate students in Taiwan. Educational Technology & Society, 20(1), 169–179.
Chuang, S. C., Lin, F. M., & Tsai, C. C. (2015). An exploration of the relationship between Internet self-efficacy and sources of Internet self-efficacy among Taiwanese university students. Computers in Human Behavior, 48, 147–155.
Crippen, K. J., & Earl, B. L. (2007). The impact of web-based worked examples and self-explanation on performance, problem solving, and self-efficacy. Computers & Education, 49(3), 809–821.
Dean, K. L., & Wright, S. (2017). Embedding engaged learning in high enrollmentlecture-based classes. Higher Education, 74(4), 651–668.
Dwyer, C. P., Hogan, M. J., & Stewart, I. (2014). An integrated critical thinking framework for the 21st century. Thinking Skills and Creativity, 12, 43–52.
Field, A. (2000). Discovering statistics using SPSS for Windows: Advanced techniques for the beginner. London: Sage.
Flanagin, A. J., & Metzger, M. J. (2000). Perceptions of Internet information credibility. Journalism & Mass Communication Quarterly, 77, 515–540.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Frazier, K., & Reynolds, E. (2012). Power up your creative mind. Marion: Pieces of Learning.
Greene, J. A., Yu, S. B., & Copeland, D. Z. (2014). Measuring critical components of digital literacy and their relationships with learning. Computers & Education, 76, 55–69.
Hofer, B. K. (2004). Epistemological understanding as a metacognitive process: Thinking aloud during online searching. Educational Psychologist, 39(1), 43–55.
Hao, Q., Wright, E., Barnes, B., & Branch, R. M. (2016). What are the most important predictors of computer science students' online help-seeking behaviors? Computers in Human Behavior, 62, 467–474.
Hocevar, K. P., Flanagin, A. J., & Metzger, M. J. (2014). Social media self-efficacy and information evaluation online. Computers in Human Behavior, 39, 254–262.
Hsieh, Y.-H., & Tsai, C.-C. (2014). Students’ scientific epistemic beliefs, online evaluative standards, and online searching strategies for science information: The moderating role of cognitive load experience. Journal of Science Education and Technology, 23(3), 299–308.
Johnson, F., Sbaffi, L., & Rowley, J. (2016). Students’ approaches to the evaluation of digital information: Insights from their trust judgments. British Journal of Educational Technology, 47(6), 1243–1258.
Jöreskog, K. G., & Sörbom, D. (1993). LISREL 8: Structural equation modeling with the SIMPLIS command language. Lincolnwood, IL: Scientific Software International.
Kayes, D. C. (2002). Experiential learning and its critics: Preserving the role of experience in management learning and education. Academy of Management Learning & Education, 1(2), 137–149.
Kelloway, E. K. (1998). Using LISREL for structural equation modeling: A researcher’s guide. Newbury Park, CA: Sage.
Kim, K.-S., & Allen, B. (2002). Cognitive and task influences on web searching behavior. Journal of the American Society for Information Science and Technology, 53(2), 109–119.
Kim, Y., & Glassman, M. (2013). Beyond search and communication: Development and validation of the Internet Self-efficacy Scale (ISS). Computers in Human Behavior, 29(4), 1421–1429.
Kim, Y., Glassman, M., Bartholomew, M., & Hur, E. H. (2013). Creating an educational context for Open Source Intelligence: The development of Internet self-efficacy through a blogcentric course. Computers & Education, 69, 332–342.
Kline, R. B. (1998). Principles and practise of structural equation modeling. New York: Guilford Press.
Kolb, A. Y., & Kolb, D. A. (2012). Experiential learning theory. In A. Y. Kolb & D. A. Kolb (Eds.), Encyclopedia of the sciences of learning (pp. 1215–1219). Berlin: Springer.
Kolb, D. A. (2014). Experiential learning: Experience as the source of learning and development. Upper Saddle River, NJ: FT Press.
Kuo, F. R., Hwang, G. J., & Lee, C. C. (2012). A hybrid approach to promoting students’ web-based problem-solving competence and learning attitude. Computers & Education, 58(1), 351–364.
Lai, C. L., & Hwang, G. J. (2014). Effects of mobile learning time on students’ conception of collaboration, communication, complex problem-solving, meta-cognitive awareness and creativity. International Journal of Mobile Learning and Organisation, 8(3), 276–291.
Lai, C. L., & Hwang, G. J. (2015). An interactive peer-assessment criteria development approach to improving students’ art design performance using handheld devices. Computers & Education, 85, 149–159.
Lei, P. L., Sun, C. T., Lin, S. S. J., & Huang, T. K. (2015). Effect of metacognitive strategies and verbal-imagery cognitive style on biology-based video search and learning performance. Computers & Education, 87, 326–339.
Liang, J. C., & Tsai, C. C. (2009). The information commitments toward web information among medical students in Taiwan. Educational Technology & Society, 12(1), 162–172.
Lin, C. L., Hou, H. T., & Tsai, C. C. (2016). Analyzing the social knowledge construction and online searching behavior of high school learners during a collaborative problem solving learning activity: A multi-dimensional behavioral pattern analysis. Asia-Pacific Education Researcher, 25(5–6), 893–906.
Molinillo, S., Aguilar-Illescas, R., Anaya-Sanchez, R., & Vallespin-Aran, M. (2018). Exploring the impacts of interactions, social presence and emotional engagement on active collaborative learning in a social web-based environment. Computers & Education, 123, 41–52.
Moos, D. C. (2014). Setting the stage for the metacognition during hypermedia learning: What motivation constructs matter? Computers & Education, 70, 128–137.
Noh, Y. (2010). A study on developing evaluation criteria for electronic resources in evaluation indicators of libraries. The Journal of Academic Librarianship, 36(1), 41–52.
Pantiwati, Y. (2013). Authentic assessment for improving cognitive skill, critical-creative thinking and meta-cognitive awareness. Journal of Education and Practice, 4(14), 1–9.
Partnership for 21st Century Skills. (2009). Museums, libraries, and 21st century skills. Washington, DC: Institute of Museum and Library Services.
Puustinen, M., Bernicot, J., Volckaert-Legrier, O., & Baker, M. (2015). Naturally occurring help-seeking exchanges on a homework help forum. Computers & Education, 81, 89–101.
Rahimi, E., van den Berg, J., & Veen, W. (2015). Facilitating student-driven constructing of learning environments using Web 2.0 personal learning environments. Computers & Education, 81, 235–246.
Raykov, T., & Marcoulides, G. A. (2008). An introduction to applied multivariate analysis. New York, NY: Taylor and Francis.
Rosman, T., Mayer, A. K., & Krampen, G. (2016). A longitudinal study on information-seeking knowledge in psychology undergraduates: Exploring the role of information literacy instruction and working memory capacity. Computers & Education, 96, 94–108.
Schraw, G., & Dennison, R. S. (1994). Assessing metacognitive awareness. Contemporary Educational Psychology, 19(4), 460–475.
Selim, H. M. (2007). Critical success factors for e-learning acceptance: Confirmatory factor models. Computers & Education, 49(2), 396–413.
Shea, P., & Bidjerano, T. (2012). Learning presence as a moderator in the community of inquiry model. Computers & Education, 59(2), 316–326.
Sung, H. Y., Hwang, G. J., Lin, C. J., & Hong, T. W. (2017). Experiencing the Analects of Confucius: An experiential game-based learning approach to promoting students' motivation and conception of learning. Computers & Education, 110, 143–153.
Tien, F. F., & Fu, T. T. (2008). The correlates of the digital divide and their impact on college student learning. Computers & Education, 50(1), 421–436.
Torkzadeh, G., & van Dyke, T. P. (2001). Development and validation of an Internet self-efficacy scale. Behaviour & Information Technology, 20(4), 275–280.
Tsai, C. C. (2004). Information commitments in Web-based learning environments. Innovations in Education and Teaching International, 41(1), 105–111.
Tsai, C. C. (2008). Standards of judging online information, searching strategies and learning outcomes from online inquiry science activities. In Y. J. Lee & A. L. Tan (Eds.), Science education at the nexus of theory and practice (pp. 135–154). Rotterdam: Sense.
Tsai, C. C., Chuang, S. C., Liang, J. C., & Tsai, M. J. (2011). Self-efficacy in Internet-based learning environments: A literature review. Educational Technology & Society, 14(4), 222–240.
Tsai, M. J. (2009). Online Information Searching Strategy Inventory (OISSI): A quick version and a complete version. Computers & Education, 53(2), 473–483.
Tsai, M. J., & Tsai, C. C. (2003). Information searching strategies in web-based science learning: The role of internet self-efficacy. Innovations in Education and Teaching International, 40(1), 43–50.
Van Acker, F., Vermeulen, M., Kreijns, K., Lutgerink, J., & van Buuren, H. (2014). The role of knowledge sharing self-efficacy in sharing Open Educational Resources. Computers in Human Behavior, 39, 136–144.
Vandewaetere, M., & Clarebout, G. (2011). Can instruction as such affect learning? The case of learner control. Computers & Education, 57(4), 2322–2332.
Wanner, T., & Palmer, E. (2015). Personalising learning: Exploring student and teacher perceptions about flexible learning and assessment in a flipped university course. Computers & Education, 88, 354–369.
Whitelock-Wainwright, A., Laan, N., Wen, D. W., & Gasevic, D. (2020). Exploring student information problem solving behaviour using fine-grained concept map and search tool data. Computers & Education, 145, 103731.
Wu, Y. T., & Tsai, C. C. (2005). Information commitments: Evaluative standards and information searching strategies in web-based learning environments. Journal of Computer Assisted Learning, 21(5), 374–385.
Xing, W. J., Ao, L. J., Xiao, H. T., & Liang, L. (2020). Chinese nurses’ preferences for and attitudes about e-learning in continuing education: A correlational study. Journal of Continuing Education in Nursing, 51(2), 87–96.
Yalcin, M. E., & Kutlu, B. (2019). Examination of students’ acceptance of and intention to use learning management systems using extended TAM. British Journal of Educational Technology, 50(5), 2414–2432.
Yukselturk, E., & Bulut, S. (2007). Predictors for student success in an online course. Educational Technology & Society, 10, 71–83.
Zhou, M. M., & Lam, K. K. L. (2019). Metacognitive scaffolding for online information search in K-12 and higher education settings: A systematic review. Etr&D-Educational Technology Research and Development, 67(6), 1353–1384.
Zhu, Y. Q., Chen, L. Y., Chen, H. G., & Chern, C. C. (2011). How does Internet information seeking help academic performance?—The moderating and mediating roles of academic self-efficacy. Computers & Education, 57(4), 2476–2484.
Zubala, A., Lyszkiewicz, K., Lee, E., Underwood, L. L., Renfrew, M. J., & Gray, N. M. (2019). Large-scale online education programmes and their potential to effect change in behaviour and practice of health and social care professionals: A rapid systematic review. Interactive Learning Environments, 27(5–6), 797–812.
Metadaten
Titel
From organization to elaboration: relationships between university students’ online information searching experience and judgements
verfasst von
Chiu-Lin Lai
Publikationsdatum
25.04.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Journal of Computers in Education / Ausgabe 4/2020
Print ISSN: 2197-9987
Elektronische ISSN: 2197-9995
DOI
https://doi.org/10.1007/s40692-020-00163-8

Weitere Artikel der Ausgabe 4/2020

Journal of Computers in Education 4/2020 Zur Ausgabe

OriginalPaper

Virtual learning communities (VLCs) rethinking: influence on behavior modification—bullying detection through machine learning and natural language processing

OriginalPaper

Direct or indirect effects from “perceived characteristic of innovation” to “intention to pay”: mediation of continuance intention to use e-learning

OriginalPaper

Students’ performance in blended learning: disciplinary difference and instructional design factors

OriginalPaper

Exploring the role of EFL learners’ online self-regulation profiles in their social regulation of learning in wiki-supported collaborative reading activities

OriginalPaper

Learners’ perceptions and experiences of studying psychology online

Premium Partner