Page 2 - R_EdQuire White Paper Nov 2017 v3.4
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EdQuire White Paper: Computer	learning	behaviour	in	K-12
                                                                                                    Nov 2017 V3.4
                                                                                                      Page 2 of 15
               1.	Introduction

               Students	and	teachers	in	Australian	classrooms	use	a	wide	range	of	computer	resources	to	facilitate	the
               learning	process	(Crook	and	Sharma	2013)	and	instil	in	students	the	ICT	and	higher	order	21 	Century	skills.
               In-class	usage	those	resources	actively	shapes	the	nation's	educational	outcomes.	However,	we	have	a
               limited	understanding	of	how	computers	are	used	in	classrooms,	of	the	categories	of	software	and	internet
               resources	that	are	utilized	to	facilitate	learning	and	of	how	both	relate	to	learning	outcomes	(Crook	and
               Sharma	2013).

               The	body	of	K-12	ICT	literature	suggests	the	emergence	of	a	second	digital	divide	between	those	with
               advanced	ICT	skills	and	those	without.	However,	the	research	has	invariably	employed	surveys,	manual	logs
               and	interviews.	This	has	prompted	calls	for	more	objective	data	on	classroom	computer	use	from	many
               educators	faced	with	stagnant	or	even	falling	educational	outcomes	and	ICT	skills	despite	the	ever	increasing
               expenditure	on	K-12	ICT	(NAP-ICT	2014).

               The	purpose	of	this	paper	is	to	report	on	objective	data	from	high	school	student	computer	use	during	trials
               of	our	EdQuire	real-time	Learning	Analytics	classroom	tool	in	four	schools.	edQuire	is	a	private	4	year
               philanthropic	project	in	collaboration	with	a	number	of	teachers	and	academics	located	in	Sydney,	Australia.
               Its	aim	is	to	use	objective	data	and	artificial	intelligence	to	make	computer	learning	processes	in	classrooms
               visible	to	teachers	and	educators,	in	order	to	forge	a	better	understanding	of	how	ICT	is	used	in	schools	and
               how	it	can	be	made	to	benefit	all	students	in	all	schools.

               This	report	is	an	observational	report	of	computer	use	by	549	Year	7-12	students	from	four	independent	high
               schools	over	one	year,	during	which	time	teachers	were	given	real-time	Learning	Analytics	data	of	each
               student’s	computer	use	and	engagement	in	a	single	glanceable	colour	coded	web	page.		We	used	an	edQuire
               background	agent	on	students'	computers	to	continuously	send	application	and	internal	activity	data	used	by
               students	during	lessons	to	our	cloud-based	data	warehouse.	Using	an	AI-based	learning	analytics	algorithm
               we	categorized	and	analysed	the	educational	relevance	of	student	computer	usage	data	in	real	time.		We
               also	continuously	displayed	this	data	to	the	teachers	on	a	web	console	their	students’	classroom	engagement
               in	the	form	of	a	glanceable	browser	screen	with	student	icons	colour	coded	according	to	their	engagement.
               Students	on	an	assigned	resource	(On-Task)	were	coded	green,	students	on	a	self-discovered	resource
               (OwnTask)	blue	and	students	off	task	(Off-Task)	red.	We	analysed	this	data	and	provided	reports	to	teachers
               on	engagement,	distractibility,	task	switching	and	search	engine	use.

               We	report	here	on	the	collected	data,	with	early	analysis,	including	by	gender	and	by	year	grade.	We	also
               report	on	a	small	prospective	controlled	substudy	examining	students’	learning	behaviour	after	giving	them
               access	to	their	own	analytics	data.

               We	present	a	preliminary	analysis	describing	computer	use	in	classrooms:	characterising	the	extent	of	active
               computer	use	in	classrooms,	the	nature	and	cognitive	level	of	activities	undertaken,	the	proportions	of	on-
               task	and	off-task	computer	use	and	an	overview	of	search	engine	use	by	students.	Finally,	we	show	that
               giving	students	feedback	of	their	own	data	can	have	a	dramatic	beneficial	effect	on	their	self-regulation.

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