Neuroscience and technology enhanced learning

Extracts from ‘Neuroscience and technology enhanced learning’ published by Futurelab.

“Neuroscientists generally believe that human learning, as in the formation of memory, occurs by changes in these patterns of connectivity between neurons – or ‘synaptic plasticity’. …. In education, of course, we think about learning in ways that extend well beyond the concept of memory. …. For that reason alone, neuroscience cannot offer anything like a complete story of learning in the classroom.”

This is not the same as saying that we should ignore the increasing discoveries of neuroscience! This report describes findings from neuroscience which may help understand how better to facilitate learning in our schools.

Vive la difference! How neuroscience helps us understand the need for differentiation and personalisation.

Hoeft et al 2008 describe “gender differences in how individuals respond to video games”. Feedback also appears to be age related. Van Duijvenvoorde 2008 suggests that older people are more influenced by negative than positive feedback. Luna et al 2004 “shows how a range of factors that are critical to successful self-regulated learning (processing speed, voluntary response suppression, and working memory) mature across different age groups”. This insight may better inform our expectations of how children of different ages can self-regulate their learning.

Digital technologies can increase pupil engagement by catering for individual differences including ability, gender and age.

Special needs can be targeted. Kucian et al 2011 “used an educational game based on neuroscientific understanding to demonstrate remediation of dyscalculia in terms of numerical performance and brain function”. Butterworth and Laurillard 2010 suggest that using digital technology to help with dyspraxia can:

• provide easily-accessed and unsupervised repeated practice
• be age-independent
• be sensitive to individual needs
• be meaningful by linking the physical to the abstract, “such as when a learner ‘zooms into’ a 1–10 number line to discover decimal numbers”
• be unthreatening
• offer feedback in an “endlessly patient fashion”.

But personalisation can go further than this. “Technology can adapt dynamically to the changing needs of the learner based on an automatic assessment of their responses.” In Graphogame, a game which teaches children to associate graphemes with phonemes, “online algorithms analyze a child’s performance and rewrite the lesson plans ‘on the fly’ depending on which specific confusions the learner shows.”  

If a picture says a thousand words … Or, two senses are better than one.

Illustrating text enhances memory (Pavio and Csapo 1973). Brain scan experiments (Beauchamp et al 2004) suggest that multimodal stimuli produce more brain activity than unimodal although the “effectiveness of multimodal presentation as a memory/ learning strategy appears to rely on whether it encourages processing related to educational objectives.” (Dubois and Vial 2000)

“Adding auditory cues to a virtual reality environment (comparing unimodal with multimodal) increased activation in the hippocampus, a region strongly

associated with memory.” (Andreano et al 2009)

Neuroscience also suggests that learners should also be encouraged to touch things. “Object recognition by touch and vision activate several overlapping and closely-related brain regions;” again this leads to enhanced brain activity.

Collaborative learning: two heads are better than one too.

“Technology is providing new opportunities to share ideas”.  Dumas et al 2010 found that “several aspects of social interaction that may support collaborative learning, such as interactional synchrony, anticipation of other’s actions and co-regulation of turn-taking, are associated with neural synchronisation between collaborators’ brains as measured by EEG.”

Other researchers (King-Casas et al 2005, Miller 2005, Boudreau et al 2009 show how trust between potential collaborators develops through reciprocity and how different contexts engender different types of trust.

Collaboration may also enhance creativity by reducing the tendency to fixate on one’s own ideas according to neuroscientific evidence from Fink et al 2010.

Do those brain training things really work?

There is “accumulating evidence” that video games enhance some cognitive skills. However, computer based ‘brain training’ does not seem to transfer to everyday learning. But Jaggi et al 2008 found that “when young adults undertook a 19-day computer-based training program that focused on developing working memory for 30 minutes a day, it was found that not only their working memory, but also their …ability to solve problems in new situations.”  

Sleep deprivation: the dark side of technology

Technology is ubiquitous and pervasive and this may pose a problem for learning.  “Sleep plays an important role in memory, so ‘when’ we learn influences ‘how well’ we learn, with better recall following a period asleep than after the same period awake. Since technology now makes it easier for us search out, learn, communicate and apply knowledge all day and all night, this access can impact negatively on our sleep. For example, hormonal developmental influences produce a phase delay in the circadian timing mechanism of teenagers, but the use of mobile technology has also been shown to contribute to their sleep loss [Van den Bulck 2004]. A recent study in the US [Calamaro et al 2009] showed the average teenager indulging in around four activities involving technology after 9.00pm, spending over an hour on each. …. Not only does sleep support our recall … it also supports our ability to make links between [new] memories and older ones, which is important for our creative functioning.” So, when access to technology impacts on our sleep habits, it can be detrimental to both our learning and our creativity.

You can access the full report here. 

References

Andreano, J., et al., 2009. Auditory Cues Increase the Hippocampal Response to Unimodal Virtual Reality. Cyberpsychology & Behavior, 12(3): p. 309-313.].

Beauchamp, M.S., et al. 2004, Integration of auditory and visual information about objects in superior temporal sulcus. Neuron 41 (5): p. 809-823

Boudreau, C., McCubbins, M.D. and Coulson, S. 2009. Knowing when to trust others: An ERP study of decision making after receiving information from unknown people. Social Cognitive and Affective Neuroscience, 4(1): p. 23-34

Butterworth, B. and Laurillard, D. 2010 Low numeracy and dyscalculia: identification and intervention. ZDM 42(6): p. 527-539.

Calamaro, C.J., T.B.A. Mason, and S.J. Ratcliffe, 2009.Adolescents Living the 24/7 Lifestyle: Effects of Caffeine and Technology on Sleep Duration and Daytime Functioning. Pediatrics, 123(6): p. E1005-E1010.]

Dubois, M. and Vial, I. 2000 Multimedia design: the effects of relating multimodal information. Journal of Computer Assisted Learning 16(2): p. 157-165

Dumas, G., et al., 2010 Inter-Brain Synchronization during Social Interaction. PLoS ONE 5(8)

Fink, A., et al., 2010. Enhancing creativity by means of cognitive stimulation: Evidence from an fMRI study. Neuroimage, 52(4): p. 1687-1695

Hoeft, F., et al., 2008. Gender differences in the mesocorticolimbic system during computer game-play. Journal of Psychiatric Research, 42: p. 253-258

Jaeggi, S.M., et al., 2008. Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences (USA), 105(19): p. 6829-6833

King-Casas, B., et al., 2005.Getting to know you: Reputation and trust in a two-person economic exchange. Science, 308(5718): p. 78-83

Kucian, K., et al., 2011 in press  Mental number line training in children with developmental dyscalculia. Neuroimage. Corrected Proof.

Luna, B., et al., 2004. Maturation of cognitive processes from late childhood to adulthood. Child Development, 75(5): p1357-1372

Miller, G., 2005 Neuroscience - Economic game shows how the brain builds trust. Science 308(5718): p. 36-36

Paivio, A. and Csapo, K. 1973. Picture superiority in free recall: imagery or dual coding? Cognitive Psychology, 5: p. 176-206

Van den Bulck, J., 2004. Television viewing, computer game playing, internet use and self-reported time to bed and time out of bed in secondary-school children. Sleep, 27 p. 101-104

van Duijvenvoorde, A.C.K., et al., 2008 Evaluating the negative or valuing the positive? Neural mechanisms supporting feedback-based learning across development. Journal of Neuroscience 28(38): p. 9495-9503

Ideas in Mobile Learning

Traxler, J. 2011 Introduction  pp 4-12 in Traxler J and Wishart J (eds) 2011 Making mobile learning work: case studies of practice Higher Education Academy Escalate Education Study Centre available at http://escalate.ac.uk/8250 accessed 10th May 2011

Mobile learning is “learning with mobile devices” including “smart-phones, games consoles, media players, netbooks and handheld computers.” (p4)

The functions of mobile learning devices include “connecting and communicating via telephone network, wireless network and Bluetooth connection; capturing and storing data that might be voice, location, position, change in position, inclination, image, video, text or number; running applications comparable to computer programs; and providing output in the form of documents, movies, music and animations.” (p4)

“By now almost everyone owns one and uses one, often more than one. Not only do they own them and use them but they also invest considerable time, effort and resource choosing them, buying them, customising them and exploiting them. These [//p4//p5//] handheld devices express part or much of their owners’ values, affiliations, identity and individuality through their choice and through their use.”

However, in “comparison with desktop PC devices and technologies, what we see is diversity, transience and incoherence.” (p5) This makes it difficult to leverage learners’ own devices.

However, mobile learning offers some distinctive advantages:

• Learning can take place as and when required (this is called ‘contingent’ learning). For example, learners can feedback their understanding of a concept by texting or twittering during a presentation or they can process fieldwork data in situ rather than retreating indoors.
• Learning can take place “in surroundings that make learning meaningful” (p6), such as in a cathedral, at sea or abroad; this is ‘situated’ learning.
• Learning can be ‘authentic’, for example doing drugs calculations on hospital wards.
• Learning can be ‘context aware’. For example when a learner is in an art gallery looking at an old master the mobile device can provide background information about the painting, the artist or the culture.
• Learning can be ‘personalised’ to the learner.
  
  

Mobile learning can reach geographically distant communities and solve the problem of sparsity allowing communities of learners to become established regardless of separation. It can reach those socially excluded such as travelers and those excluded by disability such as dyslexics.

Mobile learning can provide “extra opportunities for learning“(p8) because “mobile devices can be used in dead-time, small bursts of otherwise unused time, such as waiting in lifts, cafes, buses or queues. This is also significant as an example of bite-sized learning. Although possibly educationally limited and perhaps even educationally trivial, mobile phones will always be carried by learners whereas books or laptops might not be.”  (p8)

Cornelius, S, Marston P, and Gemmell, A 2011 SMS text messaging for real-time simulations in Higher Education pp 13-17 in Traxler J and Wishart J (eds) 2011 Making mobile learning work: case studies of practice Higher Education Academy Escalate Education Study Centre available athttp://escalate.ac.uk/8250  accessed 10th May 2011

Final year undergraduates studying Applied Geomorphology took part in a flood disaster simulation. Having read a briefing pack they were then sent a text alerting them to forecasts of heavy rain. Further texts were sent at intervals; some required them to make a decision. Their responses influenced subsequent messages. “At any time during the activity learners could seek additional information to help them make their decisions. The tutor played the role of a representative from civil defence HQ and pointed them towards further information in response to specific requests.” The simulation was assessed through a reflective blog.

Mobile learning “allowed the activity to take place in real-time, at realistic times, and beyond the normal classroom environment.”

Having constructed the decision tree with the appropriate messages the texts could be sent automatically requiring little time commitment from the tutor. This means that the exercise is scalable to virtually any size.

Learners were given the option of using email to keep their costs down but all used texts. They were unconcerned about working outside normal hours and looked forward to the messages: one said “you feel more involved in the thing because you didn’t know when you were going to get the updates …that was fun.” (p15)

Issues could involve the potential for failure (mobile networks go down from time to time) and the need for some students to turn off their phones whilst at work (or in other lessons).

Beddall-Hill, N. 2011 Postgraduates, field trips and mobile devices pp18-22 in Traxler J and Wishart J (eds) 2011 Making mobile learning work: case studies of practice Higher Education Academy Escalate Education Study Centre available athttp://escalate.ac.uk/8250  accessed 10th May 2011

“There may be problems accessing personal devices in regards to sensitive data and m-safety issues.” (p20)

Woodgate, D. Stanton Fraser D and Martin S 2011 Bringing school science to life: Personalisation, contextualisation and reflection of self-collected data with mobile sensing technologies pp 23-28 in Traxler J and Wishart J (eds) 2011 Making mobile learning work: case studies of practice Higher Education Academy Escalate Education Study Centre available athttp://escalate.ac.uk/8250  accessed 10th May 2011

“Mobile sensing enables groups of learners to collect environmental data in their local area using a simplified version of the equipment used by professional scientists. For example, pupils can collect data on parameters such as light and humidity to help them understand the reasons for variations in plant species occurring in different locations, such as under trees as opposed to open grassland, or to monitor carbon monoxide levels around their school at different times of the day, to help them understand the impact of road traffic. When such data are displayed in compelling ways, children not only gain insights into aspects of the underpinning science (which can of course be built upon in class), but can be encouraged to engage in other learning activities as well, such as discussion, presentation of their findings and report writing. Since these are activities that professional scientists engage in, they can thus gain insights into aspects of the working lives of scientists.” (p24)

Data was mashed into either Google Maps or Google Earth to provide visually compelling displays.

Is 'rip, mix, burn' a model for e-learning?

Remix: Leonardo's Last Supper reinterpreted by the Simpsons.

Manovich (2005) points out that traditionally, education flows from a source to a receiver; in education the teacher transmits knowledge to the student in the hush of the classroom.  However, in education 2.0 
knowledge is collaboratively constructed through multiple dialogues, as at a party. He sees this as the 'remixing' of knowledge and finds precedents in the merging of cultures as when Rome conquered Greece or the renaissance rediscovered the classics. 


Baraniuk (2006) notes that the LP has been superseded by a digital music culture which is characterised by a creative process of rip, mix and burn. 


Ripping is defined by wikipedia as a "process of copying". In some contexts such as where intellectual property rights exist this can be illegal.  In other cases it can be unethical (eg in an academic context unattributed copying is plagiarism).  But Blakley (2010) points out a "culture of copying" makes the fashion industry massively innovative.


Mixing or remixing is the creative part of the process.  An audio track can be remixed by breaking it down into its components, subtracting some and adding others. Shakespearean plays are often remixed by reinterpreting them into a new context; the extent to which this is done can lead to the new version being regarded simply as a new edit or as a work in its own right such as Verdi's Otello or Porter's Kiss Me, Kate. 


Burning is the process of recording the audio track.


I want to reinterpret (which is in itself a type of remixing) this process as a metaphor about learning. Specifically, I want to explore ripping as the transmissive aspect of education, mixing as the collaborative aspect and burning as the production of the end product.


Sanger (2010) explores the difference between information and knowledge. An unread text represents information but it is not until the student has learned it by reading it and understanding it in the context of the student's schema that this information becomes knowledge. The reading (the 'ripping') is not enough. The student needs to remix it by  analysing (disassembling) the text, examining each component, and then synthesising the new ideas with their own previous knowledge before it can be burned into their brain. 


Although Sanger attacks collaborative learning ("It is one thing to engage in a discussion .... but it is quite another to think creatively and critically for oneself"; p20) he is not attacking the belief that dialogues and structured conversations can facilitate learning. Considering ideas from alternative points of view is an important strategy in mixing. As Cascio (2009) suggests, a "proliferation of diverse voices may actually improve our overall ability to think." I think Sanger is saying that the iconic status of collaborative learning is blinding people to the fact that mixing is not enough; that ripping and burning are essential parts of the process of learning.

A typical student watering-hole

I think Sanger would see parallels between his ideas and those of Thornburg (2004). Thornburg  suggests that in our hunter-gatherer past there were three types of primitive pedagogy:

• The campfire around which an elder of the tribe sat and told stories which has evolved into the lecture or the presentation; 
• The watering-hole where people gossiped which has evolved into the seminar, the campus-cafe or the academic common room;
• The cave where individuals sat and thought through the long, dark, lonely nights which has evolved into the study-bedroom; for Sanger this is the "essentially solitary"  moment when learning is achieved.

Sloman (2001; p116) adds a fourth pedagogy to Thornburg's triad:

• The hunting party where young hunters honed their skills under the supervision of the old has evolved into the lab.

This is useful because there are some aspects or types of learning where discussion is not enough and where practical activities take precedence so I see Sloman's hunting-party as an alternative to or an elaboration of Thornburg's watering-hole. 

So learning appears to be a three-part process:

• Ripping at the campfire where ideas are transmitted;
• Mixing at the watering -hole or on the hunting-party where ideas are pulled apart, examined from different perspectives; and reassembled in novel ways;
• Burning in the cave where learning is consolidated.

This should also true for good e-learning:

• Information is presented to students using text, video, slide presentation or audio podcast (many authorities seem to concentrate entirely upon this transmissive, instructional process);
• The students discuss the information using chat rooms, discussion forums, wikis, or sl seminars
• The students then create their own paper, or blog, or artefact.

References

Baraniuk R 2006  Open Source learning TED talks available at http://www.ted.com/talks/lang/eng/richard_baraniuk_on_open_source_learning.html accessed 24th October 2010

Blakley J 2010 Lessons from fashion's free culture TECX USC available at http://www.ted.com/talks/johanna_blakley_lessons_from_fashion_s_free_culture.html accessed 18th October 2010

Cascio J 2009 Get SmarterAtlantic Magazine July/August 2009

Manovich, L. (2005). Remixing and Remixability. http://www.manovich.net/

Sanger, L. (2010). Individual Knowledge in the Internet Age. Educause Review, March/April 2010. pp14-24) http://net.educause.edu/ir/library/pdf/ERM1020.pdf

Sloman M 2001 The e-learning revolution: from propositions to action Chartered Institute of Personnel and Development London 0-85292-873-4

Thornburg D 2004 Campfires in Cyberspace: Primordial metaphors for learning in the 21st Century International Journal of Instructional Technology and Distance Learning 1:10 available at http://itdl.org/journal/oct_04/invited01.htm accessed 24th October 2010

wikipedia Ripping available at http://en.wikipedia.org/wiki/Ripping accessed 28th October 2010