Skip to main content
Experience
Log in to track your progress.

There are two primary benefits to infinite scrolling and streamlined navigation: enhanced learner “flow” and increased cognitive absorption.

Benefit 1: Enhanced learner “flow.”

The state of flow, a concept popularized by Csíkszentmihályi (2008), allows a user to focus solely on the task at hand and is oftentimes accompanied by a transformation of time. People experiencing a state of flow when learning online reported that they retained more information (Skadberg & Kimmel, 2004). Researchers have found that cognitive absorption and flow are closely related (Agarwal & Karahanna, 2000).

This new, infinite scrolling requires fewer clicks to navigate through. Nielsen (1994) identifies that users will generally disengage and lose interest after three clicks. Interrupting a learner’s focused attention requires additional time to get back into a state of flow (Nakamura & Csikszentmihalyi, 2009), and inconsistent navigation can disrupt a user’s flow state.

Facilitating optimal online navigation, which is characteristic of a state of flow, can:

  • Lengthen users’ online sessions (Hsu, Chang, & Chen, 2012; Koufaris, 2002)
  • Increase learning performance and positive affect (Chen, Wigand, & Nilan, 2000; Kiili, 2005; Pearce, 2005).

Inconsistent navigation also causes extraneous cognitive load (Hu, Hu, & Fang, 2017).

Benefit 2: Increased cognitive absorption.

Sweller’s (1988) cognitive load theory puts limited working memory at the forefront of instructional design. By reducing extraneous cognitive load and redirecting learners' attention to cognitive processes that are directly relevant to the construction of mental schemas, instructional designers can increase a learner’s cognitive absorption and thus understanding of a topic (Sweller, Van Merriënboer, & Paas, 1998).

Streamlining the path navigation and introducing infinite scrolling help to keep the learner oriented and focused on the content. Disorientation occurs when learners (Edwards & Hardman, 1989; Wojdymksi & Kalyanaraman, 2016):

  • Don’t know where to navigate next
  • Know where to navigate next but don’t know how to get there
  • Don’t know their current position relative to the overall structure of the environment.

Users will lose interest in websites when they experience disorientation (McDonald & Stevenson, 1998) because they become frustrated and cannot accomplish their goals (Bessière et al., 2003). In addition, navigability of an interface plays a crucial role in online information processing in that it influences (Gwizdka & Spence, 2007; Marchionini, 1997; Sundar, Kalyanaraman, & Brown, 2003):

  • users’ ability to find content
  • their capacity to process the content
  • their perceptions of the experience.

By reducing extraneous cognitive load, learners will also retain knowledge better. Learners can only retain 7(+/-2) pieces of information in their limited working memory (Miller, 1956). E-learning also requires sustained periods of attention from learners, but attentional resources are likely to be depleted more rapidly because of the cognitive tax that comes along with actively encoding and conceptualizing new information (Federman, 2019).

References:

  • Agarwal, R. & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive absorption and beliefs about information technology usage. MIS Quarterly, 24(4), 665-694.
  • Bessière, K., Ceaparu, I., Lazar, J., Robinson, J., & Shneiderman, B. (2003). Social and psychological influences on computer user frustration. In E. Bucy & J. Newhagen (Eds.), Media Access: Social and Psychological Dimensions of New Technology Use (pp. 169-192). Mahwah, NJ: Lawrence Erlbaum Associates.
  • Chen, H., Wigand, R. T., & Nilan, M. S. (2000). Exploring web users’ optimal flow experiences. Information Technology & People, 3(4), 263–281.
  • Csíkszentmihályi, M. (2008). Flow: The psychology of optimal experience. New York, NY: Harper Perennial.
  • Edwards, D. & Hardman, L. (1989). Lost in hyperspace: Cognitive mapping navigation in a hypertext environment. In R. McAleese (Ed.), Hypertext: Theory into Practice (pp. 90-105). Norwood, NJ: Ablex Publishing.
  • Esteban-Millat, I., Martínez-López, F. J., Huertas-García, R., Meseguer, A., & Rodríguez-Ardura, I. (2014). Modelling students’ flow experiences in an online learning environment. Computers & Education, 71, 111–123.
  • Federman, J. (2019). Interruptions in online training and their effects on learning. European Journal of Training and Development. https://doi.org/10.1108/EJTD-10-2018-0100
  • Gwizdka, J. & Spence, I. (2007). Implicit measures of lostness and success in web navigation. Interacting with Computers, 19(3), 472-488.
  • Hsu, C. L., Chang, K. C., & Chen, M. C. (2012). Flow experience and internet shopping behavior: investigating the moderating effect of consumer characteristics. Systems Research and Behavioral Science, 29(3), 317–332.
  • Hu, P. J. H., Hu, H. F., & Fang, X. (2017). Examining the mediating roles of cognitive load and performance outcomes in user satisfaction with a website: A field quasi-experiment. MIS Quarterly, 41(3), 975-987.
  • Kiili, K. (2005). Digital game-based learning: towards an experiential gaming model. Internet and Higher Education, 8(1), 13–24.
  • Koufaris, M. (2002). Applying the technology acceptance model and flow theory to online consumer behavior. Information Systems Research, 3(2), 205–223.
  • Marchionini, G. (1997). Information seeking in electronic environments. Cambridge, UK: Cambridge University Press.
  • Mayer, R. E. & Moreno, R. (2003). Nine ways to reduce cognitive load in multimedia learning. Educational Psychologist, 38(1), 43-52.
  • McDonald, S., & Stevenson, R. J. (1998). Effects on text structure and prior knowledge of the learner on navigation in hypertext. Human Factors, 40(1), 18-27.
  • Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97.
  • Nakamura, J., & Csikszentmihalyi, M. (2009). Flow theory and research. Handbook of Positive Psychology, 195-206.
  • Nielsen, J. (1994). Enhancing the explanatory power of usability heuristics. In Proceedings of the ACM CHI'94 Conference. Boston, MA, 152-158.
  • Pearce, J. (2005). Engaging the learner: how can the flow experience support e-learning?. In Proceedings of world conference on e-learning in corporate, government, healthcare, and higher education. Chesapeake, VA.
  • Skadberg, Y. X. & Kimmel, J. R. (2004). Visitors’ flow experience while browsing a Web site: its measurement, contributing factors, and consequences. Computers in Human Behavior, 20(3), 403-422.
  • Sundar, S. S., Kalyanaraman, S., & Brown, J. (2003). Explicating web site interactivity: Impression formation effects in political campaign sites. Communication Research, 30(1), 30-59.
  • Sweller, J. (1988). Cognitive load during problem-solving: Effects on learning. Cognitive Science, 12(2), 257–285.
  • Sweller, J., Van Merriënboer, J. & Paas, F. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10 (3), 251–296.
  • Wojdynski, B. W. & Kalyanaraman, S. (2016). The three dimensions of website navigability: Explication and effects. Journal of the Association for Information Science and Technology, 67(2), 454-464.