Making Barriers to Learning in MOOCs Visible. A Factor Analytical Approach

TEST	FIT INDICES
TEST	6-FACTOR SOLUTION	7-FACTOR SOLUTION
Chi-Square Test of Model Fit
Value	736.830	505.654
degrees of freedom	372	344
p-value	.000	.000
RMSEA
Estimate	0.046	0.045
CFI/TLI
CFI	0.956	0.963
TLI	0.934	0.940
Standardized/weighted Root Mean Square Residual
Value	0.024	0.024

Table 2

Factor loadings of the barriers (i.e. items) based on EFA on their target categories (i.e. factors) in the 6-factor solution.

ITEM DESCRIPTION	1	2	3	4	5	6
Lack of Interaction with Instructor	.753*	.188*	–.098	–.025	–.041	–.008
Lack of Instructor Presence	.645*	.240*	.023	–.056	–.005	.009
Lack of Interaction with Students	.723*	.092	–.080	.060	.062	–.022
Learning feels Impersonal	.715*	.006	.036	.011	.081	.036
Lack of Student Collaboration	.603*	–.102	.260*	–.031	.015	–.005
Prefer Face To Face Learning	.659*	–.149*	.050	.064	.030	.126*
Feeling Of Isolation	.569*	–.127*	.186	–.066	.102	.168*
Lack of Language Skills	–.047	.883*	.098*	.009	–.018	.033
Lack of Writing Skills	.035	.829*	.023	.011	.010	–.029
Lack of Reading Skills	–.009	.669*	.235*	.134*	–.038	.019
Lack of Information Literacy Skills	.132	.584*	.028	.286*	.063	–.029
Lack of Typing Skills	.028	.738*	–.082	.046	–.016	.031
Lack of Confidence	.203*	.423*	–.147*	–.061	.135*	.153*
Low Quality of the Learning Materials	–.031	.04	.855*	.048	.021	.039
Instructors Don’t Know How To Teach Online	.124*	.029	.753*	.041	–.011	.045
Course content is bad	–.032	.109*	.757*	.029	.038	.042
Course content is too easy	.117	.070	.567*	–.093	.139*	–.159*
Unavailable Course Materials	.035	.025	.578*	.200*	–.038	–.019
Lack of Clear Expectations or Instructions	.211*	.027	.565*	.038	.028	.119*
Technical Problems PC	–.106*	.050	.068	.766*	.058	.003
Lack of Software Skills	.078	–.003	.125	.571*	–.043	.117
Lack of Skills Using the Delivery System	.009	.004	.063	.663*	–.003	.175*
Lack of Adequate Internet	–.090	.058	.161*	.532*	.141*	.019
Insufficient Training To Use Delivery System	.087	.150*	.044	.492*	.093	.097
Lack of Technical Assistance	.188*	.188*	.011	.530*	.120*	–.134*
Workplace Commitments	.011	.030	–.176*	.034	.801*	.057
Workplace Issues	–.027	–.019	.091	.097	.712*	–.019
Lack of Support from the Employer	.195*	–.111	.140	.088	.545*	–.249*
Lack Time	–.082	–.132*	.024	–.210*	.484*	.339*
Too Many Interruptions During Study	.002	.106	.027	.057	.526*	.153*
Family Issues	–.078	.145*	.154	.042	.481*	–.006
Lack of Motivation	.053	.083	.083	.179*	–.036	.665*
Own Responsibility Learning	.145*	–.022	–.053	.139	.079	.610*
Procrastinate	.055	.093	.051	–.089	.143*	.549*

[i] * Statistically significant at 5% level

Note 1: Italic numbers represent items with factor loadings < .40.

Note 2: Bold numbers represent items with factor loadings > .40 onto their target factor.

Factor 1	Social interactions: These are issues to learning in MOOCs that learners perceive as being caused by the online environment such as a lack of interaction with peers and instructors, the lack of collaboration with other learners, feeling isolated or preferring face-to-face learning.
Factor 2	Academic skills: Learners perceive barriers to learning in MOOCs due to a lack of basic academic skills related to writing, reading typing and information literacy.
Factor 3	Content related issues: This factor is concerned with issues that are related to the content of the MOOC that can be experienced as barriers by learners, such as the unavailability of learning materials, a low quality of the learning materials or the lack of clear instructions in the MOOC.
Factor 4	Technical skills and problems: Learners experience barriers to learning in MOOCs due to their lack of technical skills or technical problems such as technical problems with the pc or the internet or their unfamiliarity with online learning tools, lack of skills using the delivery system or lack of software skills.
Factor 5	Situational issues: This factor is concerned with the extent to which learners experience barriers relating to a lack of time in general, family or work issues or interruptions during their study time.
Factor 6	Individual motivation: These are issues relating to learner motivation while learning in the less supported learning environment of a MOOC, such as procratination, lack of motivation or the own responsibility for learning.

Table 3

Factor labels and internal consistency value per factor.

	# ITEMS	LABEL	α
Factor 1	7	Social interactions	.867
Factor 2	6	Academic skills	.894
Factor 3	6	Content related issues	.881
Factor 4	6	Technical skills and problems	.845
Factor 5	6	Situational issues	.801
Factor 6	3	Individual motivation	.750

Table 4

CFA goodness of fit values for the 6-factor solution with and without covariation (N = 270).

TEST	FIT INDICES
TEST	NO COVARIATION	WITH COVARIATION
Chi-Square Test of Model Fit
Value	1009.783	903.388
degrees of freedom	512	508
p-value	.000	.000
RMSEA
Estimate	0.064	0.057
90% confidence interval	.058–.070	.051–.063
CFI/TLI
CFI	0.887	0.910
TLI	0.876	0.901
Standardized/weighted Root Mean Square Residual
Value	0.068	0.070

Table 5

CFA factor loadings for the 6-factor model.

ITEM DESCRIPTION	1	2	3	4	5	6
Lack of Interaction with Instructor	.677*
Lack of Instructor Presence	.691*
Lack of Interaction with Students	.604*
Learning feels Impersonal	.808*
Lack of Student Collaboration	.621*
Prefer Face To Face Learning	.691*
Feeling Of Isolation	.719*
Lack of Language Skills		.909*
Lack of Writing Skills		.840*
Lack of Reading Skills		.870*
Lack of Information Literacy Skills		.855*
Lack of Typing Skills		.730*
Lack of Confidence		.436*
Low Quality of the Learning Materials			.907*
Instructors Don’t Know How To Teach Online			.836*
Course content is bad	*		.834*
Course content is too easy			.572*
Unavailable Course Materials			.679*
Lack of Clear Expectations or Instructions			.716*
Technical Problems PC				.800*
Lack of Software Skills				.681*
Lack of Skills Using the Delivery System				.759*
Lack of Adequate Internet				.700*
Insufficient Training To Use Delivery System				.698*
Lack of Technical Assistance				.675*
Workplace Commitments					.779*
Workplace Issues					.700*
Lack of Support from the Employer					.507*	–
Lack Time					.575*
Too Many Interruptions During Study					.676*
Family Issues					.488*
Lack of Motivation						.775*
Own Responsibility Learning						.708*
Procrastinate						.630*

[i] * Statistically significant at 5% level.

Table 6

Classification of barrier factors.

FACTOR	LABEL	TYPE
1	Social interactions	Partly MOOC and partly non-MOOC related
2	Academic skills	Non-MOOC related
3	Content related issues	MOOC related
4	Technical skills and problems	Partly MOOC and partly non-MOOC related
5	Situational issues	Non-MOOC related
6	Individual motivation	Non-MOOC related

Example of (part of) a barriers to learning in MOOCs dashboard with fictional scores.

SAMPLE INFORMATION N = 540
ITEM NUMBER	ITEM DESCRIPTION	M	SD
Bar_1	LackInstructorPresence	–.91	1.011
Bar_2	UnavailableCourseMaterials	–.82	1.218
Bar_3	InstructorsDontKnowHowToTeachOnline	–.95	1.214
Bar_4	LackClearExpectationsInstructions	–.83	1.107
Bar_5	LackInCourseSupport	–.92	.997
Bar_6	LackTimelyFeedback	–.86	1.053
Bar_7	LackDecentFeedback	–.73	1.072
Bar_8	LackInteractionInstructor	–.58	1.105
Bar_9	LowQualityMaterials	–.84	1.270
Bar_10	InsuffTrainingTooUseDeliverySystem	–1.26	.946
Bar_11	LackInteractionStudents	–.82	1.048
Bar_12	LearningImpersonal	–1.10	1.021
Bar_13	FeelingOfIsolation	–1.20	.988
Bar_14	LackSocialContext	–1.16	.961
Bar_15	LackStudentCollaboration	–.90	1.075
Bar_16	PreferFaceToFaceLearning	–.62	1.212
Bar_17	LackLanguageSkills	–1.31	1.076
Bar_18	LackWritingSkills	–1.28	.973
Bar_19	LackReadingSkills	–1.39	1.020
Bar_20	LackTypingSkills	–1.51	.810
Bar_21	LackInformationLiteracySkills	–1.33	.976
Bar_22	LackOfConfidence	–1.21	1.003
Bar_23	LackSoftwareSkills	–1.37	.958
Bar_24	LackSkillsUsingDeliverySystem	–1.36	.916
Bar_25	UnfamiliairWithOnlineLearningTools	–1.36	.980
Bar_26	Procratinate	–.06	1.269
Bar_27	LackMotivation	–.38	1.279
Bar_28	OwnResponsibilityLearning	–.35	1.286
Bar_29	LearningEnvironmentNotMotivating	–.71	1.120
Bar_30	FamiliyIssues	–.90	1.152
Bar_31	WorkplaceIssues	–.69	1.173
Bar_32	LackTime	.31	1.240
Bar_33	LackSupportFamilyFriends	–1.28	.924
Bar_34	LackSupportEnmployer	–.92	1.242
Bar_35	TooMayInterruptionsDuringStudy	–.43	1.159
Bar_36	LackAdequateInternet	–.98	1.294
Bar_37	LackTechnicalAssitance	–1.16	.950
Bar_38	CourseContentTooEasy	–.88	1.069
Bar_39	CourseContentTooHard	–.90	1.010
Bar_40	CourseContentBad	–.95	1.211
Bar_41	TechProblemsPC	–1.24	1.053
Bar_42	TechProblemsSite	–1.23	1.021
Bar_43	WorkplaceCommittments	–.21	1.311
Bar_44	InsufficientAcademicKnowledge	–1.03	1.033

[i] Note: Items were measured on a 5-point Likert scale (–2 = not at all, 2 = to a very large extend).

References

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Articles in this issue

DOI: https://doi.org/10.5944/openpraxis.13.2.124 | Journal eISSN: 2304-070X

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Language: English

Page range: 143 - 159

Submitted on: Oct 18, 2020

Accepted on: May 31, 2021

Published on: Oct 20, 2021

Published by: International Council for Open and Distance Education (ICDE)

In partnership with: Paradigm Publishing Services

Keywords:

barriers to learning,

online learning,

MOOCs,

open education,

factor analysis

© 2021 Maartje Henderikx, Karel Kreijns, Kate M. Xu, Marco Kalz, published by International Council for Open and Distance Education (ICDE)
This work is licensed under the Creative Commons Attribution 4.0 License.

Volume 13 (2021): Issue 2

Making Barriers to Learning in MOOCs Visible. A Factor Analytical Approach

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