Abstract: Market-driven transformation of higher education has focused on content development and technology integration enabling students to access vast amounts of information and individuals for interaction. However, the increase in activity has not led to an increase in learning. Overwhelmed with too much information and lacking the ability to use technology for learning, student engagement is limited to the surface level of information transfer. Cognitive overload provides insight into why this takes place and the premise for suggesting a greater emphasis on instruction in the technology conversation. Instruction is necessary to provide students with the context and skills that they need to make the tool of technology useful for learning.
Keywords: pedagogy, content, technology, TPACK, connectivism, cognitive overload, information, instruction, interaction
Though it once occupied the central place in the university experience, instruction seems to have been displaced by an emphasis on outputs in conversation of change in higher education. Pursuit of measurable outputs has led to an emphasis on business operations (Ernst & Young, 2011), the development of content and programs for employability (Knight & Yorke, 2003), and most importantly the use of technology (Barnes & Tynan, 2007) to meet expected demands of Generation Y students for a digital learning experience (Sternberg, 2012). A recent survey of professors revealed that the operational principles governing their work clearly demonstrate that the value of instruction has been marginalized in favor of more measurable outputs like research (Field, 2015).
Meanwhile educational institutions continue the trend toward differentiation in terms of technology use despite numerous reports that technology does not necessarily have a positive impact on student performance. The British Journal of Technology recently published an analysis of a range of data measuring the impact of various technologies on student outcomes, which found there was no consistent relationship (Lei, 2010). Instead, the data showed that technology integration produced a range of effects from positive to negative and had no direct correlation to GPA. Some unknown factor determined whether or not technology use would result in learning for the students.
Literature Review (The Problem)
One reason that technology integration has not automatically enhanced student performance is that students and teachers alike struggle to use technology for the purpose of learning. Assuming that students expect novel and extensive use of technology in their learning experiences, universities have embraced technology in a way that decries consistent evidence that students don’t know how to use it effectively for learning (Sternberg, 2012). In terms of connectivist pedagogy, this is a dangerous scenario. The rapidly changing nature of knowledge has made the student’s ability to access and process information stored in digital repositories more valuable than the development of a broad knowledge base that will soon be outdated (Siemens, 2005). Depending on how it is used, the internet can be an excellent platform where students can develop these learning skills, but it can also devolve into little more than a channel for transferring information (Schank, 1998). Unfortunately, the emphasis of technology integration has focused on content and administration rather than on learning purposes (Brown, Dehoney, & Millichamp, 2015), and students are expected to be familiar with using technology for the purposes of learning (Diaz, 2010) even though the teachers are still unsure of what this would look like (Bull, et. al, 2008). Thus, the dramatically increased level of access to information and interaction in the online environment has not led to the same kind of increase in the amount of learning taking place (Swan, 2002).
On the other hand, widespread use of web 2.0 technology has altered the way that students think in ways that may not be beneficial to the learning process. The social, connected, bite-size, instant-access stream of information that constantly bombards and distracts its users eventually damages their ability to participate in deep, focused, reflective learning (Carr, 2011; Trapnell, Sinclair, & Immordino-Yang, 2012). Unable to think in a linear fashion, students enter the online or offline learning environment expecting constant change, distraction, and stimulus (Ally, 2004). Individuals who experience this constant demand on their attention may completely lose their ability for deep engagement or fail to develop this cognitive ability altogether (Imordino-Yang, Christodoulou, & Singh, 2012).
In a non-linear learning context students only have time or interest to ask ‘what happened’ or ‘how to do this’ before moving on to the next bit of information (Ibid). This is representative of Piaget’s early stages of cognitive engagement which does not move beyond concrete representations to abstraction and personalization (Piaget, 1964). Sadly, the design of the learning experience seems to follow the downward progression of student ability rather than the other way around as course facilitators upload the content, activate the discussion boards, and open the class to learners who have no idea how to use these resources effectively. The “quick burst” transactions that have resulted enable a kind of rote learning identified by the lowest of the six levels included in Bloom’s taxonomy (Mayer, 2002).
Given the inevitable constraints of time and mental endurance, even students who have the ability to evaluate or reflect on the meanings and implications of information will find it hard to resist the temptation to skim across the surface of multiple resources and interactions rather than diving deeply into a few. This trade-off of depth for breadth of learning often results in less-than-meaningful experiences (Mayer, 2002). Studies indicated a significant, but negative relationship between course completion and the amount of interaction between learners (Grandzol & Grandzol, 2010). The number of discussions that students have to pay attention to is also negatively correlated with their satisfaction in the learning environment. Some other factor is needed to transform greater access to information and interaction into greater amounts of learning.
Literature Review (Potential Solutions)
If education is meant to be anything more than the simple transfer of information, then students must somewhere encounter the chance to develop skills for deeper levels of thinking and higher levels of cognitive engagement. Information literacy, as defined by The American Library Association (ACRL, 1989), goes beyond the simple ability of knowing how to identify words. It requires some ability to screen and evaluate the text, the meaning, the context, and the implications of what is written. The internet, provides students with access to a vast pool of resources for information and interaction, but students need some kind of instructional guidance to apply these toward a productive educational outcome (Woo & Reeves, 2007).
In response to the chaotic nature of progressive schools, Dewey (1953) suggested that constructivist learning was not meant to exist independently of all oversight. Rather, instructors were needed to guide the process of exploration in a positive and worthwhile direction. Depending on their level of ability, students may need greater levels of instruction to take advantage of learning opportunities (Kirschner, Sweller & Clark, 2006). The amount of instructional support that students will need to manage the excessive amount of information and interactions available online will vary depending on the person. Some people are better prepared to handle greater amounts of information and ambiguity than others (Mulder, dePoot, Verwij, Janssen & Bijlosma, 2006). Additionally, some technology environments require less cognitive capacity from learners than others (Reeves, 1999).
The question that educators must consider is whether they must adapt their teaching methods to the ability of students (Barnes & Tynan, 2007) or whether they can design their approach to help students develop their abilities to engage in the reflective and linear thinking required for deep understanding. A useful starting point for the design of learning experiences that require students to exercise higher levels of cognitive complexity may be found in Bloom’s Taxonomy. Mayer used this framework to suggest 19 kinds of cognitive processes that teachers can use to guide students toward the creative end of the learning spectrum where ‘meaningful learning’ takes place (2002).
Additional suggestions for the design of an effective technology-based learning experience include interactive instructors, dynamic discussions, and clear consistent course structures (Swan, 2002). Yet, the opportunities for information and interaction should not be overwhelming as demonstrated by previous research. Further suggestions include the importance of giving students the opportunity reflect, develop abstract understanding, and personally apply the information that they encounter if they want to engage more deeply (Immordino-Yang, Christodoulou & Singh, 2012). The value of instruction is its ability to limit the scope of student effort in the most productive manner.
These features require additional time and come at the necessary expense of some informational breadth. However, as recognized previously, developing the process of learning is more important than mastering the information set. The content and technology are not as important as the use that students make of these resources (Woo & Reeves, 2007). The cognitive processes developed through deeper levels of engagement will retain their value much longer than a knowledge base of rapidly expiring content. However, the development of these processes will require some level of instruction.
As online learning technology continues to enhance, extend, and empower the education process (Smyth, n.d.) it is vital for educators and students to consider the importance of pedagogy in making this tool useful for learning. It would be detrimental to higher education continue to make the mistake of confusing information and interaction for education. Fortunately, it is quite likely that the trend toward an overreliance on content and technology is coming to an end. Progressive educators like Dewey (1938) and Montessori (2004) saw an application of their ideas that resulted in chaotic classrooms and effectively argued that experiential learning with social and didactic tools still requires some kind of over-arching structure in order to be effective. Today, several voices have recognized the chaos of online learning separated from instruction and suggested models like TPACK to provide over-arching structure for the use of technological tools (Jenson, 2015; Mishra & Koehler, 2006).
Instruction plays a significant role in enabling students to use technology for learning. This guidance can be embedded within the technology itself (Reeves, 1999) or within the design of technology-based instruction (Swan, 2002). Those students that are not part of a formal institution of higher education may find it valuable to connect with a learning community in which their use of technology can be guided in a coherent fashion toward increasing levels of cognitive complexity. In other words, “The role of the teacher is essential to facilitating the process and providing the learners with the resources and kinds of activities that will help them to build knowledge collaboratively, using the internet” (Harasim, 2012, no page). Perhaps it is time to re-emphasize the important role of instruction for students who want to maximize their use of technology for learning both online and in the classroom.
The causes of ineffective learning are not limited to student in higher education. It is quite possible that you are bombarded with information overload on a regular basis. If you wish to personalize some of the concepts in this report, please proceed through the following steps.
- Read This Article for an overview of some features of information overload
- Complete This One Minute Survey to find out what features of information overload others struggle with. Be sure to view the results at the end.
- Think about your most frustrating experience with information overload, then read through the “Potential Solutions” section again. How can you apply these ideas to overcome your next encounter with information overload?
Search for an online learning course (e.g. “learn to code”). Then consider the following:
- How many search results did you get back?
- How will you decide which results are worth looking at?
- How will you make your decision about which resource to use?
- Compare this process to asking an expert which resource to use? What are the pros and cons of this alternative?
- What kind of guidance would you need to make this process simpler or more accessible? (This is the most important question as it should help you discover some instructional steps you can apply to helping others learn with technology.
ACRL. (1989). Presidential Committee on Information Literacy: Final Report. Retrieved from http://www.ala.org/acrl/publications/whitepapers/presidential
Ally, M. (2004). Foundations of educational theory for online learning. In Anderson, T. & Elloumi, F. (Eds), Theory and practice of online learning (pp 3-31). Athabasca, Canada: Creative Commons: Athabasca University.
Barnes, C. & Tynan, B. (2007). The adventures of Miranda in the brave new world: learning in a Web 2.0 millennium. Research in Learning Technology, 15(3), 189-200.
Brown, M., Dehoney, J., & Millichap, N.. (2015). What’s Next for LMS? EDUCAUSE Review 50(4) Retrieved from http://er.educause.edu/articles/2015/6/whats-next-for-the-lms
Bull, G., Thompson, A., Searson, M., Garofalo, J., Park, J., Young, C., & Lee, J. (2008). Connecting informal and formal learning experiences in the age of participatory media. Contemporary Issues in Technology and Teacher Education, 8(2), 100-107. Retrieved from http://www.citejournal.org/vol8/iss2/editorial/article1.cfm
Carr, N. (2011). The shallows: What the Internet is doing to our brains. San Francisco, CA: WW Norton & Company.
Dewey, J. (1938). Experience and education. New York, NY: Macmillan.
Diaz, V. (2010). Web 2.0 and emerging technologies in online learning. New Directions for Community Colleges, 2010(150), 57-66.
Ernst & Young. (2011). Higher education and the power of choice. Retrieved from http://www.ey.com/Publication/vwLUAssets/Higher_education_and_the_power_of_choice_Australia/$File/Higher%20education%20and%20the%20power%20of%20choice%20Australia.pdf
Immordino-Yang, M. H., Christodoulou, J. A., & Singh, V. (2012). Rest is not idleness implications of the brain’s default mode for human development and education. Perspectives on Psychological Science, 7(4), 352-364.
Grandzol, C. J., & Grandzol, J. R. (2010). Interaction in online courses: More is not always better. Online Journal of Distance Learning Administration, 13(2), 1-18.
Harasim, L. (2012). Learning theory and online technology. New York, NY: Routledge.
Jenson, K. (2015). Behind the Screens. Unpublished manuscript. Retrieved from http://www.academia.edu/12279274/Behind_the_Screens_Developing_a_Digital_Learning_Literacy
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching.Educational psychologist, 41(2), 75-86.
Knight, P. T., & Yorke, M. (2003). Employability and good learning in higher education. Teaching in Higher Education, 8(1), 3-16.
Lei, J. (2010). Quantity versus quality: A new approach to examine the relationship between technology use and student outcomes. British Journal of Educational Technology, 41(3), 455-472.
Mayer, R. E. (2002). Rote versus meaningful learning. Theory into practice,41(4), 226-232.
McArthur, J. (2011) Reconsidering the social and economic purpose of higher education. Higher Education Research and Development, 30(6), 737-749.
Mishra, P., & Koehler, M. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054.
Mitra, S. (2007, February). Sugata Mitra: Kids can teach themselves [Video file]. Retrieved from http://www.ted.com/talks/sugata_mitra_shows_how_kids_teach_themselves?language=en
Mokhtar, I. A., Majid, S., & Foo, S. (2008). Information literacy education: Applications of mediated learning and multiple intelligences. Library and Information Science Research, 30(3), 195-206. doi:10.1016/j.lisr.2007.12.004
Montessori, M. (2004). The Montessori method: The origins of an educational innovation: Including an abridged and annotated edition of Maria Montessori’s The Montessori method (G. Gutek, Ed.). Lanham, MD: Rowman & Littlefield.
Mulder, I., de Poot, H., Verwij, C., Janssen, R., & Bijlsma, M. (2006, November). An information overload study: using design methods for understanding. In Proceedings of the 18th Australia conference on Computer-Human Interaction: Design: Activities, Artefacts and Environments (pp. 245-252). ACM, 2006.
Oliver, M. (2005). The problem with affordance. E-Learning and Digital Media, 2(4), 402-413.
Pacific Northwest National Laboratory (n.d.). Compfight [photo]. Retrieved from https://www.flickr.com/photos/36016325@N04/6310387725/”
Piaget, J. (1964). Development and learning. In R.E. Ripple & V.N. Rockcastle (eds.), Piaget Rediscovered (pp.7-20). Retrieved from http://www.psy.cmu.edu/~siegler/35piaget64.pdf
Reeves, W. (1999). Learner-centred design: A cognitive view of managing complexity in product, information, and environmental design. Thousand Oaks, CA: Sage Publications.
Schank, R. C. (1998). Horses for courses. Communications of the ACM, 41(7), 23-25.
Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1), 3-10.
Smyth, K. (n.d.). 3E Framework [Blog post]. 3E Education. Retrieved from http://3eeducation.org/3e-framework/
Strauss, V. (2012). Does Khan Academy know how to teach? The Washington Post. Retrieved from: https://www.washingtonpost.com/blogs/answer-sheet/post/how-well-does-khan-academy-teach/2012/07/27/gJQA9bWEAX_blog.html
Swan, K. (2002). Building learning communities in online courses: The importance of interaction. Education, Communication & Information, 2(1), 23-49.
Trapnell, P., Sinclair, L., & Immordino-Yang, M. H. (2012). Can Too Much Texting Make Teens Shallow? In K. Doheny (Ed.), Report presented at Society for Personality and Social Psychology 13th Annual Meeting (Jan 26-28, 2012) San Diego, CA. Retrieved from http://teens.webmd.com/news/20120203/cantoomuchtextingmakeyouthshallow?print=true 4/4
Vincent-Lancrin, S. (2004). Building futures scenarios for universities and higher education. An international approach. Policy Futures in Education, 2(2), 245-263.
Woo, Y., & Reeves, T. C. (2007). Meaningful interaction in web-based learning: A social constructivist interpretation. The Internet and higher education, 10(1), 15-25.