Page 1 - R_EdQuire White Paper Nov 2017 v3.4
P. 1

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

               EdQuire	White	Paper:

               Computer	learning	behaviour	in	year	grades	K-12

               Nov	2017
               FIC	Technology	Pty	Ltd	and	Edquire	International	Pte	Ltd.
               Authors:	FIC	Technology	Research	Staff,
               Author	for	Correspondence:	Dr	Michael	Cejnar,

               	 ABSTRACT:	Students	and	teachers	in	Australasian	K-12	classrooms	utilise	a	wide	range	of	computer
               	 resources	 to	 facilitate	 the	 learning	 process	 generally	 and	 instil	 21 	 Century	 skills	 specifically.

               However,	we	have	very	limited	understanding	of	how	students	use	their	computer	time	and	whether

               	 feedback	 about	 the	 usage	 can	 improve	 learning.	 Using	 a	 background	 app	 installed	 with	 students’
               	 knowledge,	FIC	Technology	collected	into	our	cloud	database,	real-time	metadata	on	the	computer
               	 application	and	online	resources	used	by	students	in	classrooms.	Student	computer	activities	were

               	 classified	and	analysed	using	an	Al-based	learning	analytics	algorithm	and	delivered	to	class	Teachers
               	 a	glanceable,	colour-coded	display	showing	each	student	as	either	On-Task	(green)	or	Off-Task	(red).

               	 Using	an	AI-based	learning	analytics	engine,	we	classified	and	analysed	educational	activities,	while
               	 providing	teachers	with	a	glanceable	colour-coded	display	of	each	student	being	either	on-assigned
               	 task	(green)	or	off-task	(red).

               We	studied	549	students	(52%	girls)	across	years	7-12	from	4	independent	schools,	capturing	21,454

               lessons	 where	 computers	 used	 from	 January	 to	 November	 2017.	 On	 average,	 students	 spent	 on

               	 average,	17%	of	this	time	off-task		but	20%	of	students	spent	30%	of	their	time	off-task.		The	majority
               	 of	computer	time	(>30%)	was	spent	on	word	processing.	Boys	spent	marginally	more	time	off-task,

               mostly	 on	 gaming.	 Girls	 were	 most	 distracted	 by	 streaming	 videos.	 	 Furthermore,	 the	 analysis	 of

               	 Internet	searching	skills	revealed	an	overwhelming	and	use	of	standard	Google	searches	with	only
               	 3%	of	searches	using	advanced	tools.

               	 When	we	gave	students	access	to	their	own	data,	a	self-selected	group	with	higher	off-task	times
               	 viewed	 the	data	 and	markedly	reduced	 their	 off-taskness	and	 distractibility.	 Our	 unique	 data	and

               analysis	 provides	 new	 and	 needed	 insights	 into	 computer	 use	 in	 classrooms	 and	 may	 facilitate

               	 student	self-regulation.

               	 Keywords:	Student	engagement,	Digital	Learning,	Learning	Analytics,	AI,	Formative	Feedback,	Self-regulation,
               Computer	learning

               ©	Copyright	2017	|	All	Rights	Reserved	by	FIC	Technology
   1   2   3   4   5   6