Classroom Computers are Not TVs

Introduction

When our students are left alone on computers (mobile or otherwise), their learning suffers for at least four reasons (according both to current research and our experience):

• our students are still learning how to learn, so they benefit significantly more from participation with an active guide;
• peer learning is not optimized when there are zero peers involved;
• screen-based technology demonstrates a reverse effect on education unless you put a program in place that requires active conceptualizaton (instead of passive zoning); and
• our students tend to navigate away from their assigned program or website (which, in addition to safety, is one reason that their computer use is to be monitored by an adult partner).

While the research in question was not conducted in special education classrooms, it is nonetheless applicable to our risk analyses.

This page is not intended to be a rigorous research article, but rather it is a risk analysis. Evidence abounds to support the portrayal of those risks (e.g., Hume, et al, 2010; Dong, et al, 2012; Turel, et al, 2014; Wilmer, et al, 2016; and so on); in comparison, there are no valid studies to demonstrate any student benefits whose value might justify a decision to pose those associated risks of harm.

(And please remember: a classroom iPad is never a reward.)

Learning How to Learn

Various research (of which Falloon, 2013, is just one example) suggests that students should participate with a partner who is experienced enough to promote learning, precisely because: a) students are still learning how to learn, and b) apps tend to be pretty awful when it comes to guiding learning (as they do in all of the categories that Falloon lists… see them digested in the discussion). Therefore, it is only when you know and trust a particular piece of software in a particular device environment (i.e., one that controls for distractions, and so on) that a partner is less crucial.

Montrieux (2015) is qualitative in nature (and performed on a small group); however, it acts as a nice starting point in your independent pursuit of the related research.

Montrieux says (among many other things) that partnership isn’t a matter of whether a person is sitting with the student at the time, but rather how much time the designer of the curriculum (software or traditional) put in beforehand on being an “innovative” partner rather than merely an “instrumental” one. The more innovative the designer, the lower the risks of isolation, distraction, inexperienced learner skills, and so on, while the student is using the program. This is apt without regard to the benefits that might be added by social interaction during the program’s use.

This highlights an already obvious principle: if you are not personally guiding a student’s learning, then you have to trust the software to take your place. So don’t leave a student alone to use a program unless you can support your trust in its design.

Software is just a medium, that is to say, a conveyance for the information: even the most trusted scaffold for learning guidance would be of no use if the conveyed content were garbage. In such a case, the lesser problem would be that of the student working alone.

In contrast, if the content were meaningful, and presented in a form that was actively designed to be more palatable to the student specifically without the need for immediate personal guidance, then the student might get something out of it just by using it on their own… which is all the better if they have been taught the skills necessary to be more than just a passive consumer of information. That is all translatable to special education venues, but tends to mean that our students will generally need personal guidance even with apps designed with good structure.

Peer Learning

Hattie (2009) synthesizes over 800 meta-analyses related to educational achievment, and when it comes to the educational use of computers, Hattie hits the high points as follows:

“An analysis of the meta analyses of computers in schools indicates that computers are used effectively (a) when there is a diversity of teaching strategies; (b) when there is a pre-training in the use of computers as a teaching and learning tools [sic]; (c) when there are multiple opportunities for learning (e.g. deliberative practice, increasing time on task); (d) when a student, not teacher, is in “control” of learning; (e) when peer learning is optimized; and (f) when feedback is optimized.”

In regards to working alone on the computer, then, part “e” is particularly germane; that is to say, while there are lots of ways to optimize peer learning, we know that the most fundamental of such principles is this: include peers.

It seems like that would be true no matter how we sliced it, except for the following: some students have impoverished peer skills, social anxieties, and the like. The opportunity to participate first in relative isolation can build confidence (with appropriate chaining), and so on; that said, the general rule is still that peer involvement is the best goal, when it is optimized á là Hattie (and when the associated software is not garbage).

Active Conceptualization

Video presentation of information is a tool, whether the screen is a TV, computer monitor, interactive whiteboard, or bedsheet. As with any tool, there are uses and abuses, so there are restrictions around allowing online access for a student, whether or not it is part of their dedicated device use. The point is to avoid passive zoning and engage active conceptualization.

There are all manner of studies showing that brain activity can dampen significantly during passive screentime activities. Conceptualization in particular gets taken offline. Our advanced training for intensely special educators makes it clear how important it is that we scaffold conceptualization skills for our students, including all of the underlying precursors:

1. Access must be of limited duration. On an iPad, this can be controlled through a timer on Guided Access, or with an external timer. This session gets measured by time (see #2), and not by whole video or episode.
2. Access must be of appropriate proportion. There must be an economy that the student has already learned to use, with (a) at least 3 parts work per earned viewing session (and preferably 5 parts), and (b) no more than 5 minutes of video or music before more work is required. (Warning: if you restrict all video/music access while you are training the student to follow the economy, rather than just the on the device, then you run a significant risk of training the student to hate the economy.) If the student’s Behavior specialist approves a different viewing time and/or ratio, then that’s fine, but you need to make sure that other students don’t think that they also get the same thing.
3. If the host district issues a warning about exceeding their bandwidth restrictions, then submit a Desktop Assistance Request  so that the issue can be addresses. This has only rarely been a problem.

If you use a set of videos instead of online access, then #3 is not an issue.

In some cases, metrics retrieved from dedicated devices have shown that several full episodes of a show are being watched per day. Please don’t let that happen. In such cases, the device has had to be removed as it was an inappropriate tool.

Monitor all Student Online Access

All student online access must be directly monitored by adult staff, whether for academics or leisure. That partner must make sure that the student is only viewing allowed sites and materials, or is only listening to music that is appropriate for school.

Lane ESD Technical Services will not automate this monitoring with filters and so on, as those techniques are not reliable. (So don’t ask.)

We also want the student’s more general access to be equitable, namely when that access is not associated with their dedicated tool use. We want our students to have access to materials that compare favorably to whatever is available to their general education peers; for example, if students in general are allowed to watch videos online during their leisure time, then we want our students to be able to do so as well (while observing the monitoring restrictions). That is not the same thing as watching videos on their dedicated devices (ever), or on similar classroom devices (if that will cause confusion for anyone).

Just to be clear, however: no leisure viewing (i.e., using computers as toys) can be allowed in the classroom when it risks losing their academic value (i.e., using computers as tools). We do have students for whom computers are not available for academics – sometimes for years on end – because they learn to refuse their use as anything other than toys.

The teacher can decide to trust a specific student to be safe online, but if that student is caught betraying their trust, then that will be the teacher’s problem to solve. In contrast, the decision to risk losing the computer’s academic value is only to be made by the IEP team.

Media access is not allowed on a student’s dedicated device, except as defined by a program that is developed by an associated specialist (i.e., AT or AAC).

Related Research

With the exception of a few specific references cited above, the remainder of these works are listed as threads for interested persons to follow. The term “teacher” in the summaries refers more generally to any licensed curriculum or therapy design professional.

Askell-Williams & Lawson MJ. (2005a). Representing the dynamic complexity of students’ mental models of learning in order to provide ‘entry points’ for teaching. New Horizons in Education, 113, 16–40. [In designing effective intervention, teachers should figure out how their students are congitively modelling the process of learning.]

Askell-Williams, Lawson MJ & Tran TAT. (2007b) Learners’ mental models about learning are multidimensional, temporally changeable, and situationally acute. In Galwye VN (Ed.), Progress in educational psychology research. Hauppauge, NY: Nova Science.

Askell-Williams, Lawson MJ & Skrzypiec G. (2012) Scaffolding cognitive and metacognitive strategy instruction in regular class lessons. Instructional Science, 40, 413.

Chi MTH, Bassok M, Lewis MW, Reimann P & Glaser R. (1989) Self-explanations: How students study and use examples in learning to solve problems. Cognitive Science, 13, 145–182. [Self-explanation helps a student to completely encode instructions, and move away from a reliance on examples.]

Dong G, DeVito EE, Du X, & Cui Z. (2012) Impaired inhibitory control in ‘Internet addiction disorder’: A functional magnetic resonance imaging study. Psychiatry Research: Neuroimaging, 203, 153–158.

Falloon G. (2013) Young students using iPads: App design and content influences on their learning pathways. Computers & Education, 68, 505-521. Elsevier.

Bendixen LD & Florian CF (Eds). (2013) Personal Epistemology in the Classroom: Theory, Research, and Implications for Practice. Cambridge University Press. [This book explores the contribution of a child’s or adolescent’s classroom on the development of their personal beliefs around knowledge and knowing.]

Hattie J (2009) Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement Routledge.

Hattie J & Yates GCR. (2014) Visible Learning and the Science of How We Learn. Routledge.

Hume C, Van Der Horst K, Brug J, Salmon J, & Oenema A. (2010) Understanding the correlates of adolescents’ TV viewing: A social ecological approach. International Journal of Pediatric Obesity, 5, 161–168. [“Interventions should target parents’ TV viewing behaviors and aim to amend habitual, ‘mindless’ TV viewing among adolescents.”]

Joram E. (2007) Clashing epistemologies: Aspiring teachers’, practicing teachers’, and professors’ beliefs about knowledge and research in education. Teaching and Teacher Education, 23, 123–135. [As teachers gain experience, they increasingly learn that educational knowledge can be generalized and falsified. Curriculum moves from ontological realism (rigid, permanent, class-generic absorption of objective facts) to relativism (flexible, changing, student-tailored sharing of subjective experiences explored through problems and inquires).] Our advanced training additionally adopts an ontologically relativist perspective.]

Kiewra, K. A. (2002) How classroom teachers can help students learn and teach them how to learn. Theory into Practice, 41, 71–80. [Even into college, students need significant instruction in learning to learn.]

Montrieux H, Vanderlinde R, Schellens T & De Marez L. (2015) Teaching and Learning with Mobile Technology: A Qualitative Explorative Study about the Introduction of Tablet Devices in Secondary Education. Public Library of Science (PLOS).

Oblinger DG & Oblinger JL (Eds.) (2005) Educating the Net Generation. Educause.

Ravizza SM, Uitvlugt MG, Fenn KM. (2016) Logged in and Zoned Out: How Laptop Internet Use Relates to Classroom Learning. Psychological Science, 28, 1-10.

Rohrer D & Pashler H. (2010) Recent research on human learning challenges conventional instructional strategies. Educational Researcher, 39, 406–412. [Commonly held perceptions are wrong about what actually promotes durable learning: a) testing is a more effective activator of learning than other forms of study, b) learning takes longer than convention suggests, and c) you should mix together different types of practice problems.]

Sweller J. (2006) The worked example effect and human cognition. Learning and Instruction, 16, 165–169. [Worked examples have value.]

Turel O, He Q, Xue G, Xiao L & Bechara A. (2014) Examination of neural systems sub-serving Facebook “addiction”. Psychological Reports: Disability & Trauma, 115, 675–695.

Wilmer HH & Chein JM (2016) Mobile technology habits: Patterns of association among device usage, intertemporal preference, impulse control, and reward sensitivity. Psychonomic Bulletin & Review, 23, 1607–1614.

Winne PH & Hadwin AF. (1998) Studying as self-regulated learning. Hacker DJ, Dunlosky J & Graesser AC (Eds.), Metacognition in educational theory and practice (pp. 277–304). Hillsdale, NJ: Erlbaum. [This is a cognitive model of studying.]

Woolfolk-Hoy A & Tschannen-Moran M. (1999) Implications of cognitive approaches to peer learning for teacher education. In A. King & A. M. O’Donnell (Eds.), Cognitive perspectives on peer learning (pp. 257–283). Mahwah, NJ: Erlbaum.