1. Educational technology (Post 2) Digital Realities

Summative course for Masters of  Education Portfolio 

Educational technology (Post 2)

1. What are the main ideas  I have learned in my readings from various books, articles and from both informal and formal experiential,social, and online learning ?

Students who spend more time socializing do so with the exclusion of engaging in academic tasks thus showing poorer academic performance in schoolwork (Junco & Cotton, 2011, p. 512).  Others however, state that task switching causes inefficiencies in performance when returning to the primary task, but has benefits if it is secondary and passive, since it can provide pause to enable renewed focus (Spink & Waller, 2008 p. 108).  Multitasking and digital technologies are being used incorrectly in educational settings and can impair learning and retention of data in most students.  In the fields of educational and clinical psychology, it has been well established that there is a “cognitive bottleneck” in the prefrontal lobes where higher order thinking occurs, and there is increased competition for an individual’s attention between one or more tasks (Wood, et al., 2011, p. 366).  Even if a learner is alert to the task at hand, and actively willing and able to selectively choose to which information it is important to attend, if attention is divided, then rapid switching between tasks will cause cognitive overload.  As a result, students will not encode or remember all the things to which they attended (Junco & Cotton, 2012, p. 505).  Imperfect selection of information means that the data is not fully accessible for later accurate retrieval or for use in higher order cognitive activities.  The performance decrements are worse when the two mental processing tasks, competing for limited working memory resources, are similar (Wood et al., p. 366).  For instance, listening to music and trying to listen to the instructor would be more taxing on working memory that listening to the instructor while viewing images on Facebook (Junco & Cotton, 2012, p.512).  It is apparent from research that educators will have to be aware of these impairments to learning and retention in order to be help students effectively engage with classroom material.

Students’ perception of ease of use of digital technologies, coupled with the ubiquity and range of activities available on digital devices, have shown that learners, especially young adults, will engage in off-task behaviors both in and out of instructional environments (Wood et al., 2011, p. 365; Junco & Cotton,  2012, p. 511).  Students have self-reported being off-task with digital technologies 43% of the time in controlled experiments with approximately even amounts of the remaining participants choosing to be super-multitaskers, and thereby even less engaged, or non-users, avoiding the technology altogether (Wood et al., 2011, p. 369 Sana et al., p. 25).  Research also indicates that Instant Messaging (IM’ing), and its successor, texting, is by far the worst arrestor of the cognitive processes for a multitasking learner in any setting (Junco & Cotton, 2011, p. 371).  More definitive research could be done using eye-tracking technologies or direct observation via video recording instead of self-reporting to better assess complete attentional focus (Sana et al., p. 29; Zhang et al., 2013, p. 29).  But, it is clear that in formal or informal learning settings, students are at a distinct disadvantage with multitasking and digital technologies no matter how adept they are, or perceive themselves to be, due to the evidence seen.  They will continue to disengage with difficult learning tasks by multitasking or choosing off-task activities.

Multitasking in any learning environment affects quality of learning and retention of even simple information. In an institutional setting, learning is hampered by multitasking and by not mentally attending or focusing on informational input.  Multitasking might hamper higher order tasks that involve understanding material and application of material to novel situations” (Wood et al. 2011, p. 366).  Even worse for learning is that in the relaxed, unsupervised home setting, where there are frequently no controls on usage of digital technology there is a frenzy of task switching and all the associated data loss and imperfect mental encoding.  This is where studying supposedly takes place.  Internationally, non-culturally bound information exists suggesting that lower GPAs and poorer academic performance may be a result of less studying because of the strong negative relationship between time spent on computers and the amount of time studying (Wentworth & Middleton, 2014 p. 310).  If multitasking and off-task activities teachers hamper simple information in any learning environment will continue to be at a disadvantage with getting students to engage with difficult and arduous reading and writing tasks.

Motivation is a big factor in off-task activities in all learning environments. Intrinsic and extrinsic motivators are: perceived efficiency; enjoyment; and the desire to use technology to learn are all linked to socializing and relationships when learning using digital technologies (Zhang et al., 2013).  More research is needed to ascertain whether students at all levels of education are learning socially or using social connections as avoidance mechanisms to academic engagement.  Given the poor results of engagement in online Massive Online Open Courses (MOOC) (Konnikova, 2014, para. 6), it is clear that teachers need to develop more social relationships in order to connect to students in digital learning settings and to keep them motivated to be on task with the learning tasks presented.  Otherwise, socializing and other cognitively low-cost activities will trump academic engagement when in competition for students’ attention. With status quo digital course design and delivery, motivation for enjoyment and socializing will keep learner disengaged in the classroom.

The effects of multitasking has impact, even on those who are quite successful in both online and offline learning. Studies to date are inadequate, but suggest that effective student e-learning engagement and skills sets mirror those of effective learners in general (Winter et al., 2010, p. 72).  The authors showed that Ph.D. students are successful learners already, and have success in learning using traditional skills which correlates with effective online learning and time management skills needed to be successful as an e-learning online milieu.  Because the Doctorate students sample is better able to seek information and educational resources offline, they experience more success doing the same online. The learning cohort used technology differently based on successful strategies that were not technology based.  Also is has been shown that those who used sophisticated strategies in offline environments practiced successful attention management in digital learning settings (Sánchez, et al., p. 553-4).  Even students that can transfer highly successful skills to the online environment still remain cognitively ineffective and less cogent then they might be without the distractions of multitasking (Frontline, [Video file], Digital Nation, 2010).

Multitasking in educational settings affects not only the active participant but also those in close proximity. Stanford University researchers and others have concluded that “multitasking on a laptop poses significant distraction to both the users and fellow students and can be detrimental to comprehension of lecture content” (Sana et al., p. 24).  New York University social media theorist Clay Shirky, an early proponent of digital technology use in educational settings, has now changed the rules from ‘allowed unless by request’ to ‘banned unless required’ because of the distraction and negative impact technology is having on those who are not choosing to use it (Shirky, 2014, para. 5).  Many educators are now in agreement that it is unfair to place other students at a learning disadvantage because of the choices of their peers.

It is becoming evident that continual attention arrest for socializing is deleterious to all persons, whether an expert or novice to digital technologies; the cost to society being the inability of learners to formulate cogent, reasoned ideas or follow lengthy or complex instructions.  Additionally, there is evidence that deep reading is in jeopardy because of media-driven cognition, with its emphasis on speed and discouragement of deliberation in both thinking and reading.  The brain’s plasticity may be at risk of being rewired due to the ubiquity of digital media and information overload (Wolf, & Barzilli, 2009, p. 33). This does not bode well for today’s digital learner in the more complex and information-saturated learning environment of the 21^st century.  Educators are expected to make information more palatable for the new learning paradigm and in fact, we should be doing the opposite by building in more complexity and difficulty to challenge learners and expand their thought processes, not bring them to a lowered learning baseline.  Removing socializing and procrastination inside of the period of work; focusing on educational tasks instead of attentional arresting technologies; and maximizing engagement with learning objects are tasks  to which we as educators and learners will have to put greater efforts.

Due to digital technology’s ubiquity, novelty, and the false premise that technology makes learning more efficient, many learners’ behavioral conditioning in non-instructional settings is to accept many small rewards for many menial digital tasks, such as emailing and posting thoughts to social media (Levitin, 2014, p. 15.70).  This reward system is becoming manifest in the learning setting at all levels as a non-cultural indicator of how students wish to learn and how they perceive valuable learning to be presented (Wentworth & Middleton, 2014 p. 310).  It will have disastrous consequences for learning as ‘continuous partial attention’ continues as the standard in classrooms unchecked and unmonitored (Stone, 2002-2014, [What is continuous partial attention] para.1).  Multitasking and unregulated or unsupervised use of digital technologies in an educational setting will dictate changes in the way we teach and learn if we wish to minimized distraction and maximize attention to material for retention and use at Bloom’s higher taxonomic levels.  Educators will have to make course content that runs counter to this behavioral conditioning which appears to be taking precedence both in and out of a formal learning environments.

Some authors state that students will have to accept responsibility for their own learning but can be included in the process by creating classroom etiquette rules or restricting access in classes to course-based websites only (Sana et al., p. 30).  The technology for culling and presenting information from the vast database that is the World Wide Web and presenting it a ‘walled-garden’ (an Intranet) has existed  since the earliest days of the Internet.  These methods have seldom been used because they are seen as either limiting in scope and breadth, or because they eliminate the serendipity that comes from surfing the web.  In fact, they are exactly the tools needed so teachers can collate and deliver many resources in a non-distracting, focused, multi-modal way while eliminating the distractive elements of online learning.  Other solutions for educators have been suggested such as instructors being given help to compete with Facebook, Twitter and texting by “developing enriching, informative and interactive classes…” (Sana et al., p. 30).  This method of enrichment seems idealistic, given the current workloads of teachers and professors without remuneration or time off in lieu of work done.  Additionally, the lack of familiarity with creation tools for teachers is a hindrance for even teachers who are technologically inclined.  Teachers’ perceptions of the efficiency of delivery methods other than technology, and value judgements as to the return on investment of multiple means of delivery for those who might possibly engage, have to be take into account before there is large scale adoption  Teachers are not instructional designers.  Another measure to insure engagement is the Personal Learning Communities (PLC) which incorporates socializing and learning in less formal setting, and leaves it to the student to engage, if they choose, asynchronously. Other initiatives include flipped classrooms and blended learning environments.  These also put the onus on the students to engage with course material, and free up time for the teacher to be the facilitator of knowledge acquisition, rather than the content expert. Institutions and administrators will have to be less technologically Utopian to make sure that educational technology are being used correctly in service to students and by extension to society.  Even if legions of teachers will create multiple means of access to interesting lesson material, the responsibility will ultimately fall to the individual learner to engage, focus and rail against the predominate easy route of multitasking and reward.

Frontline, (2010), [Video File]. Digital Nation. Producer-Director Rachel Dretzin. Retrieved June 21 from http://www.pbs.org/wgbh/pages/frontline/digitalnation/view/

Junco, R., & Cotton, S. R. (2011). Multitasking behavior. Computers & Education, 56(2), 370-378. doi:10.1016/j.compedu.2010.08.020 Retrieved from Academic Search Premier database.

Junco, R., & Cotton, S. R. (2012). No A 4 U: The relationship between multitasking and academic performance. Computers & Education, 59(2), 505-514.

        dx.doi.org/10.1016/j.compedu.2011.12.023 Retrieved from Academic Search Premier database.

Konnikova, M., (2014). Will MOOCs be flukes? Retrieved June 14, 2015, from http://www.newyorker.com/science/maria-konnikova/moocs-failure-solutions.

Levitin, Daniel J., (2014). The organized mind: Thinking straight in the age of information overload. [Kindle Edition]. Retrieved from Amazon.ca

Sana, F., Weston, T., & Cepeda, N. J. (2013). Laptop multitasking hinders classroom learning for both users and nearby peers. Computers & Education, 62, 24-31. doi:10.1016/j.compedu.2012.10.003 Retrieved from Academic Search Premier database.

Sánchez, J., Salinas, A., Contreras, D., & Meyer, E. (2011). Does the new digital generation of learners exist? A qualitative study. British Journal of Educational Technology, 42(4), 543-556. doi:10.1111/j.1467-8535.2010.01069.x

Selwyn, N., (2104). Distrusting educational technology: critical questions for changing times. New York, NY: Routledge.

Shirky, C., (2104). Why I just asked my students to put their laptops away. Retrieved June 9, 2015, from https://medium.com/@cshirky/why-i-just-asked-my-students-to-put-their-laptops-away-7f5f7c50f368

Spink, A., Cole, C., & Waller, M. (2008). Multitasking behavior. Annual Review of Information Science and Technology, 42(1), 93–118. doi:10.1002/aris.2008.1440420110.Retrieved June 9, 2015 from http://onlinelibrary.wiley.com/doi/10.1002/aris.2008.1440420110/pdf

Stone, L. (2002 - 2014). Continuous partial attention. Retrieved June 9, 2015, from http://lindastone.net/qa/continuous-partial-attention.

Wentworth, D. K., & Middleton, J. H. (2014). Technology use and academic performance. Computers & Education, 78, 306-311. doi:10.1016/j.compedu.2014.06.012 Retrieved from Academic Search Premier database.

Winter, J., Cotton, D., Gavin, J., & Yorke, J. D. (2010). Effective E-learning? multi-tasking, distractions and boundary management by graduate students in an online environment.

Research in Learning Technology, 18(1), 71-83. Retrieved June 14^, 1025, from http://www.researchinlearningtechnology.net/index.php/rlt/article/view/10753/12376

Wood, E., Zivcakova, L., Gentile, P., Archer, K., De Pasquale, D., & Nosko, A. (2012). Examining the impact of off-task multi-tasking with technology on real-time classroom learning. Computers & Education, 58(1), 365-374. doi:10.1016/j.compedu.2011.08.029 Retrieved from Academic Search Premier database.

Zhang, Y., Mao, M., Rau, P. P., Choe, P., Bela, L., & Wang, F. (2013). Exploring factors influencing multitasking interaction with multiple smart devices. Computers in Human Behavior, 29(6), 2579-2588. doi:10.1016/j.chb.2013.06.042 Retrieved from Academic Search Premier database.