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Differential effi cacy of the resources used in B-learning environments

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Background: Learning is increasingly frequent in B-Learning spaces. It is therefore necessary to study the characteristics that guarantee deeper and more successful learning in these learning environments. Method: We work with sample of 233 university students using the Moodle 3.1 platform in the third year of their degrees in Health Sciences. The effectiveness of four types of B-Learning on Learning Results (LR), behaviors on the platform, and student satisfaction are all studied. Prior knowledge is also used as a covariable. Results: It was found that the B-Learning environment in which the students obtained better general Outcomes Learning Results (LR) and a higher degree of satisfaction was the one that included the use of infographics and virtual laboratories based on Self-Regulated Learning (SRL). Conclusions: The design of B-Learning environments together with the use of SRL, is a factor that enhances effective learning and increases student satisfaction, especially if they include infographics and virtual laboratories. In addition, the use of these resources implements better overall LR on a larger number of students. Likewise, it promotes more homogeneous groups in the general LO. Future investigations will be aimed at verifying these results in other knowledge branches.
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María Consuelo Sáiz Manzanares, César Ignacio García-Osorio, José Francisco Díez-Pastor
170
Over recent decades, the use of Blended Lear ning (B-Learni ng)
environments is increasingly frequent in both state-regulated
and non-regulated education. These environments are managed
with Learning Management System (LMS). Both imply an
important challenge in the research of learning processes. Among
others, we may highlight the studies of Azevedo (2014) on Self-
Regulated Learning (SRL) that are based on the theoretical work
of Zimmerman & Moylan (2009) applied to hypermedia learning
environments. In particular, Taub & Azevedo (2019) found
signi cant differences among student users of the LMS in the
application of cognitive and metacognitive skills, taking account
of the level of previously acquired knowledge. The students with
high levels used more complex cognitive and metacognitive skills
for its resolution. These results are essential for the design of
personalized systems of intelligent tutoring.
Thus, the design of an LMS can be diverse and can include
different resources that are to do with strengthening the quality of
learning (Margulieux, McCracken, & Catrambone, 2016). These
resources mean that multi-channel information can be gathered,
which will facilitate the study of the traceability of cognitive,
affective and metacognitive skills (Azevedo et al., 2013). These
learning spaces also make the analysis of SRL processes possible
for both individuals and collectives. The advantage of these spaces
is that they provide the teacher will a lot of information through
different registries (eye-tracking, thinking aloud, note taking and
drawing, log- les, and facial recognition, among others). This eld
of investigation is known as Advanced Learning Technologies
(ALTs). Learning spaces in the 21st century therefore have to
include technological resources that encourage the development of
SRL, metacognitive instruction, and monitoring. One of the most
effective tools is MetaTutoring (Azevedo et al., 2013) that can be
implemented through d ifferent hypermedia resourc es (quizzes with
automated feedback, vir tual laboratories, infographs, etc.). They all
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Differential ef cacy of the resources used in B-learning environments
María Consuelo Sáiz Manzanares, César Ignacio García-Osorio, José Francisco Díez-Pastor
Universidad de Burgos
Abstract Resumen
Background: Learning is increasingly frequent in B-Learning spaces. It
is therefore necessary to study the characteristics that guarantee deeper
and more successful learning in these learning environments. Method:
We work with sample of 233 university students using the Moodle
3.1 platform in the third year of their degrees in Health Sciences. The
effectiveness of four types of B-Learning on Learning Results (LR),
behaviors on the platform, and student satisfaction are all studied. Prior
knowledge is also used as a covariable. Result s: It was found that the
B-Learning environment in which the students obtained better general
Outcomes Learning Results (LR) and a higher degree of satisfaction was
the one that included the use of infographics and virtual laboratories
based on Self-Regulated Learning (SRL). Conclusions: The design of
B-Learning environments together with the use of SRL, is a factor that
enhances effective learning and increases student satisfaction, especially
if they include infographics and virtual laboratories. In addition, the use
of these resources implements better overall LR on a larger number of
students. Likewise, it promotes more homogeneous groups in the general
LO. Future investigations will be aimed at verifying these results in other
knowledge branches.
Keywords: Blended learning B-learning, virtual labs, infographics, self-
regulated learning (SRL), learning outcomes.
E cacia diferencial de los recursos empleados en entornos B-learning.
Antecedentes: es cada vez más frecuente que el aprendizaje se realice
en espacios B-Learning. Por ello, es preciso estudiar cuáles son las
características que garantizan en estos entornos aprendizajes más
profundos y exitosos. Método: se trabajó en la plataforma Moodle 3.1
con una muestra 233 estudiantes universitarios de tercero de grado en la
rama de Ciencias de la Salud. Se estudió la efectividad de cuatro tipos de
B-Learning sobre los Resultados de Aprendizaje (RA), las conductas de
aprendizaje y la satisfacción de los estudia ntes. Asimismo, se utilizó como
covariable los conocimientos previos. Resultados: se halló que el entorno
B-Learning en el que los estudiantes obtuvieron mejores RA generales
y mayor grado de satisfacción fue el que incluía el uso de infografías y
de laboratorios virtuales basados en aprendizaje autorregulado (SRL).
Conclusiones: el diseño de entornos B-Learning, junto con la utilización
de SRL, es un factor que potencia aprendizajes e caces e incrementa
la satisfaccn de los estudiantes, especialmente si incluyen infografías
y laboratorios virtuales. Además, el uso de estos recursos implementa
mejores RA generales en un mayor número de estudiantes. Futuras
investigaciones irán dirigidas a comprobar estos resultados en otras ramas
de conocimiento.
Palabras clave: blended learning (B-learning), laboratorios virtuales,
infografías, aprendizaje autorregulado, resultados de aprendizaje.
Psicothema 2019, Vol. 31, No. 2, 170-178
doi: 10.7334/psicothema2018.330
Received: December 2, 2018 • Accepted: March 26, 2019
Corresponding author: María Consuelo Sáiz Manzanares
Facultad de Ciencias de la Salud
Universidad de Burgos
09001 Burgos (Spain)
e-mail: mcsmanzanares@ubu.es
Differential efficacy of the resources used in B-learning environments
171
have the purpose of providing feedback to the learner for problem-
solving tasks that help monitoring: focalization of the object of the
task, activation of previous knowledge, searching for strategies to
resolve the problem, evaluation throughout the problem-solving
process, changes if needed to the problem-solving strategy, and
nal evaluation (Taub & Azevedo, 2019). Those resources respect
the learning pace of the student, facilitating personalization (Sáiz,
García-Osorio, Díez-Pastor, & Martín, 2019).
From among all the possible registers, it is worth highlighting
the behavioral patterns in the learning process. Among them,
information can be obtained on: frequency of access of the
student to the platform and the use of resources (Cerezo, Sánchez-
Santillán, Paule-Ruiz, & Núñez, 2016).
Likewise, recent studies (Sáiz, Marticorena, García-Osorio,
& Díez-Pastor, 2017) have pointed to a greater effectiveness of
B-L earning spaces i n which 80% of the teach ing is done in virt ual
environments and 20% is done Face to Face (F2F). Along these
lines, other researchers have indicated that the effectiveness of
these spaces will increase, if they include hypermedia resources
(videos, quizzes, forums…) (Cerezo et al., 2016) and active
methodologies such as Project-Based Learning. (PBL) (Bannert,
Reimann, & Sonnenberg, 2014). With regard to the hypermedia
resources, among the most novel is the use of infographs. These
graphs display informat ion and can include: words, phrases, images,
and videos. If they include images and interactive resources they
can be especially effective. It seems that they facilitate dynamic
conceptual understanding of the subject matter among students
(Al-Dairy & Al-Rabaani, 2017). In addition, they increase the
motivation and the creativity of the students (Damman, Vonk,
van den Haak, van Hooijdonk, & Timmermans, 2018; Papic &
Sušilović, 2018). In summary, the infograph is considered a low-
cost resource that i mproves conceptual understand ing and retention
(Kiernan, Oppezzo, Resnicow, & Alexander, 2018; Nogueira-
Frazão & Martínez-Solana, 2019) and problem-solving (Santos,
Pereira-Neto, & Neves, 2019). In addition, this resource facilitates
the development of SRL and re ection on the contents under study
(Balkac & Ergun, 2018). It has likewise been demonstrated that
the infograph increases its effectiveness, if it contains questions
for SRL (Haşlaman, 2018; Santos et al., 2019). Along these lines,
this resource is administered to achieve personalized learning
among the students (Gutiérrez, Barriga, Ramírez-Corona, López-
Malo, & Palou, 2016).
Another novel hypermedia resource in B-Learning spaces, is
the use of virtual laboratories. Alves et al. (2016) and Viegas et al.
(2018) af rmed that their implementation can improve teaching
in a virtual as well as a presential mode. The virtual laboratory
has especially been applied as a resource in the disciplines of
Engineering and the Health Sciences. The advantages of its use
are the personalization of teaching and cost reductions (Viegas et
al., 2018). This tool strengthens re exive learning based on the use
of metacognitive skills and SRL (Achuthan, Francis, & Diwakar,
2017). In addition, the virtual laboratory has shown itself to be
more effective that the presential laboratory (Koretsky, Kelly, &
Gummer, 2011). The reasons are centered on the improvement of
conceptual understanding with this tool, increased SRL, and the
use of metacognitive skills. It all increases student motivation,
satisfaction, and performance (Viegas et al., 2018). However, the
weak point of this resou rce is excessive individuality in t he learning
process. Authors such as Gustavsson et al. (2009) therefore advise
combining its use with collaborative actions such as PBL.
In summary, the use of infographs and virtual laboratories
in B-Learning spaces appears to increase the personalization of
learning and to strengthen SRL in real time (Krum, 2014; Kunze,
& Rutherford, 2018; Harley, Taub, Azevedo, & Bouchet, 2018). In
addition, personalization increases learning results and student
interaction with the platform (Sáiz, Marticorena, Díez-Pastor, &
García-Osorio, 2019).
Equally, the emergence of this type of resource, with
increasingly greater celerity, makes it necessary to evaluate its
effectiveness in the learning process, in the light of different
quality standards: metacognitive design, technological knowledge
and content (Vongkulluksn, Xie, & Bowman, 2018). In turn, each
one of them contains a series of sub-standards that are described
in Table 1.
Xie, Di Tosto, Chen, & Vongkulluksn (2018), in a meta-analysis
on the quality of teaching in different B-Learning environments
found high correlations between the evaluation of teaching
materials and metacognitive structure in their design. Moreover,
they found lower correlations between the valuation of the mater ials
and the technological structure, for their implementation on the
platform. These results point to the importance of using friendly
interfaces (Sáiz, Cuesta, Alegre, & Peñacoba, 2017). Furthermore,
different researchers (Cerezo, Bernardo, Esteban, Sánchez,
& Tuero, 2017) pointed out that the use of SRL in university
environments increases student satisfaction with the teaching.
Moreover, as previously mentioned, the LMS includes tools that
register the interactions with the different agents involved in the
teaching. Nevertheless, the majority of these environments include
no tools for the analysis of these data (Xie, Kim, Cheng, & Luthy,
2017) making the inclusion of plugins necessary (Luna, Castro, &
Romero, 2016).
In view of the studies referred to above, which place emphasis
on the rapid incorporation of technological resources at the service
of learning in B-Learning spaces, especially in the teaching of
H ig he r Ed uc a ti on , i t a pp e ar s re le va nt t o e va lu at e th ei r ef fe c ti ve ne ss
in real educational environments (Wiley, Bliss, & McEwen, 2014).
In particular, the effectiveness of different B-Learning designs
is examined in this work that implement different learning
Table 1
Standards of quality in the evaluation of hypermedia resources adapted from
Xie, Di Tosto, Chen, & Vongkulluksn (2018) p. 95
Quality standards of
materials Sub-standards
Metacognitive design
Adjustment of proposed activities
Well-developed monitoring
Feedback throughout the process
Inquiry-based activities
Scaffolding
Depth of learning is well developed
Well-worked content
Clarity of objectives
Conceptual progression
Differentiation between concepts
Adaptation of the level worked in the presentation of
the concepts
The development of critical thought
Technological structure
Personalization
User-friendliness
Channels of communication
Interactivity
María Consuelo Sáiz Manzanares, César Ignacio García-Osorio, José Francisco Díez-Pastor
172
resources, prepared with different technological tools (infographs,
virtual laboratories, videos, quizzes, process-oriented automatic
feedback, and PBL) applied in different combinations.
The research questions were as follows:
RQ1 Are there signi cant differences in student learning
results in different B-Learning environments?
RQ2 Are there signi cant differences in student learning
behaviors in different B-Learning environments?
RQ3 Are there signi cant differences in student
satisfaction in the different B-Learning environments?
Method
Participants
The study had a sample of 233 students from the third year of
degree courses in Health Sciences (see Table 2) in two subjects:
subject 1 (Group 1 and Group 3) and subject 2 (Group 2 and Group
4). Tea chin g was i mparte d by the sam e tea che r, an exp ert i n vir tu al
teaching, to all four groups.
The criteria for the inclusion of the student in the study was
systematic participation in the course work with an acceptable
presential and/or virtual participation of 85% to 100%. The
exclusion criteria were non-systematic participation on the course
(less than 80%). The assignation of the groups was done using
convenience sampling in accordance with the possibilities of
intervention. In Table 3, the characteristics of each group can be
seen, as described in the section on procedure. Likewise, the logs
in each of the groups were: Group 1 = 4064, Group 2 = 4982,
Group 3 = 10111, and Group 4 = 13433.
Instruments
Learning Strategies Scale (ACRAr) by Román and Poggioli
(2013). In this study the Scale of Metacognitive Skills was
applied. It has an inter-judge reliability of α = .90, a content
validity of r = .88, and a construct validity of r = .88. In this
study, the value found was α = .70.
Questionnaire: on previous knowledge prepared ad hoc
with 8 questions measured on a Likert-type scale of 1 to 5
on the key concepts of the subjects. In subject 1, (Groups 1
and 3) achieved a reliability index of α = .89 and in subject
2 (Groups 2 and 4) of α = .91.
Learning Management System (LMS). In this study a
Moodle v.3.1 -based LMS was used. Different hypermedia
resources were included (videos, quizzes, infographs,
and simulation laboratory) in different combinations as a
function of the groups under study, see section on procedure.
Likewise, logs were analyzed on the following indicators
of behavior on the platform: 1. Access to complementary
information; 2. Access to guidelines to carry out PBL; 3.
Access to information on theoretical content; 4. Access to
feedback from the teacher; 5. Mean number of visits per
day.
Teaching support videos: prepared ad hoc and published
in the Institutional Repository of University of Burgos
(Sáiz, 2018a, 2018b). In Group 2 and in Group 3, two
videos were used on the contents of the study units in
which self-regulation strategies were used, by the teacher,
to guide conceptual comprehension, and inter-relations.
Likewise, after the presentation of each concept, a
comprehension quizz was administered with feedback on
the responses.
The two videos used in Group 4 treated the content of the
study unit, which included self-regulation strategies. In this
case the comprehension (quizz) questions were done after
watching the video and included process-oriented feedback
(the reason for the correct response was indicated) on the
responses from the students.
Table 2
Descriptive statistics in the different groups under study with respect to the
independent variables assigned to gender and age
Group N PK
Men Women
nM
age SDage NM
age SDage
1 58 2.68 9 24.67 4.12 49 23.82 5.10
2 63 2.00 7 22.00 1.73 56 24.02 4.98
3 55 2.40 6 22.00 1.55 49 22.53 2.34
4 57 2.39 8 24.63 7.50 49 22.33 1.96
Note: PK = Previous knowledge; Group 1 = B-Learning [20 (BL)-80% (F2F)] methodology;
Group 2 = B-Learning [80 (BL)-20% (F2F)] methodology + videos + quizzes + product-
oriented feedback; Group 3 = B-Learning [80 (BL)-20% (F2F)] methodology + videos
+ quizzes + process-oriented feedback + infographs + virtual laboratory; Group 4 =
B-Learning [80 (BL)-20% (F2F)] methodology + videos + quizzes + process-oriented
feedback; Mage
= Mean Age; SDage = Standard Deviation Age
Table 3
Description of the groups under study
Resources Group 1 Group 2 Group 3 Group 4
Use of the virtual platform (LMS) 20% 80% 80% 80%
Use of videos with product-oriented quizzes on the virtual platform (LMS) No Yes No No
Use of videos on the virtual platform (LMS) No No Yes Yes
Use of quizzes on paper Yes N o No No
Use of process-oriented comprehension quizzes on the virtual platform (LMS) No No No Yes
Use of a virtual laboratory through the virtual platform (LMS) No No Yes No
Use of infographs on the virtual platform (LMS) No No Yes No
Use of quizzes for the evaluation of conceptual content with product-oriented feedback on the virtual platform (LMS) No Yes No No
Use of quizzes for the evaluation of conceptual content with process-oriented feedback on the virtual platform (LMS) No No Yes Yes
Note: PBL methodology was applied in all groups
Differential efficacy of the resources used in B-learning environments
173
Quizzes: in the four groups under study, evaluation
questionnaires on the contents of the quizz format were
used. The multiple-choice test-type questions offered four
possible responses and only one true option. The quizzes
were administered at the end of each thematic unit. In Table
4, the different options may be seen that were applicable to
the groups in the study (see Figure 1 and Figure 2).
Infographics: prepared with free Piktochart software,
a resource used only in Group 3. The structure of the
infograph consisted in the presentation of key thematic
concepts through images. Then, self-regulation questions,
which guided the responses through key images, were
included on the concepts that had been seen. Subsequently,
the question was asked “are you clear about those concepts”.
If the response was negative, the question was asked “which
are you not clear about?” The infographs are published
under open access and held in the Repository of University
of Burgos (Sáiz, 2018c, 2018d, 2018e).
Table 4
Options for the administration of the evaluation questionnai res in the groups under study
Group Group 1 Group 2 Group 3 Group 4
Form of administration On paper
On the LMS
X
X
X
X
Type of feedback to the response
Product-oriented (right-wrong) X
Product- oriented (right-wrong) (see example in Figure 1) X
Process-oriented (correct-incorrect and
orientation on the reason why) (see example in Figure 2) X X
Response time of the results One week
Immediate at the end of the questionnaire
X
X
X
X
Figure 1. Quizz with product-oriented feedback administered to groups 1 and 2
Figure 2. Quizz with process-oriented feedback administered to groups 3 and 4
María Consuelo Sáiz Manzanares, César Ignacio García-Osorio, José Francisco Díez-Pastor
174
Virtual labor atories: use was made of two virtual lab oratories
designed from a simulation structure that provided the
student with help in the form of a guide to prepare the project
(PBL). Those laboratories were structured around SRL
and the teacher guided the different practices by applying
modeling techniques and self-instructions for solving the
tasks. The steps for solving the task were recorded on video.
The student could access this resource over the platform,
whenever needed.
Learning results: the learning results from different tests
were considered: Preparation of the PBL, Defense of the
PBL, Quizzes, and Learning Results, Totals.
Scale of satisfaction with teaching activity. This instrument,
based on the work of Marsh (1987), called Student Evaluation
of Educational Quality (SEEQ) was adapted by Bol, Sáiz,
& Pérez (2013). Their scale contains ve clusters for the
analysis of teaching quality: materials, continuous evaluation,
motivation of the teacher, course workload, and the degree of
general satisfaction. It has a general index of reliability of α
= .92. Likewise, the one found for this study was α = .86.
Procedure
A multi-group design was used with pre-treatment measures
(equaling the metacognitive skills of the group), and subsequently
in the learning results, learning behavior, and student satisfaction,
considering the previous knowledge as a co-variable, in order to
control the perceived dif culty.
In Group 1, a B-Learning (20% in el LMS and 80% F2F)
teaching methodology was used, without hypermedia resources
and the quizzes were done on paper, see section on instruments.
In Group 2, a B-Learning (80% on LMS and 20% F2F)
teaching methodology was applied. In addition, the group included
hypermedia resources:
a. Videos on the contents of the subject matter that
included quizzes, the responses to which received
product-oriented feedback.
b. Quizzes for the evaluation of the contents, which were
done on the LMS with process-oriented feedback: see
instruments section.
In Group 3, a B-Learning teaching (80% LMS and 20% F2F)
methodology was administered and the following hypermedia
resources were included:
a. Videos on the contents of the subject matter that
included quizzes after treating each concept, similar
to those applied to Group 2.
b. Quizzes for the evaluation of the contents, which were
done on the LMS with process-oriented feedback; see
instruments section.
c. A virtual ad hoc laboratory; see instruments section.
This material was made available to the students from
the third week of the semester.
d. Infographs: previously described.
In Group 4, a B-Learning teaching (80% LMS and 20% F2F)
methodology was administered and the following hypermedia
resources were used:
1. Vid eos prepared ad hoc, without questions and quizzes in
the video. However, the student after watching the video
could complete a comprehension quizz-type questionnaire
that could be repeated as many times as desired.
2. Quizzes for the evaluation of the contents, which were done on
the LMS with process-oriented feedback, described earlier.
Data analysis
Before starting the study, the homogeneity of the groups
under the variable ‘use of metacognitive skills’ was analyzed.
A xed-effects ANOVA (type of group) was applied to test the
variable metacognitive skills measured on the ACRA Scale of
Metacognitive Skills ACRA, F(3, 233) = 1.251, p = .292, η2 = 0.02.
It was also studied whether differences existed at the level of
previous knowledge of the students, for which purpose a xed-
effects ANOVA (type of group) was completed. In this case,
signi cant differences were found between the groups, F(3, 229) =
14.13, p = .00, η2 = 0.16, due to which this variable was considered
a co-variable. The research questions were tested with ANCOVAS.
All these analyses were done on the statistical software package
SPSS v.24, applying a con dence interval of 95%.
Results
A xed-effects A NCOVA (type of B-L earning) was applied to test
RQ1 on the different learning results (PBL preparation, PBL defense,
Quizzes, and Learning Results (LR) totals). Signi cant differences
were found in all the LR and the effect values were measured,
following the classi cation of Cohen (Kelley & Preacher, 2012),
in the LR for the quizzes (η2 = 0.45), in the LR on the preparation
of the PBL (η2 = 0.31), and in the LR Totals (η2 = 0.20). Likewise,
the differences in the Bonferroni test were found for all the groups
except in the LR, in the defense of PBL, and between Groups 3 and
4 in the LR on the quizzes (see Table 5). However, the covariable
previous knowledge had effects of the LR Quizzes, F(1, 228 ) = 67.24, p
= .000, η2 = 0.47 and not on the other results [LR preparation of PBL
F(1, 228) = 0.38, p = .54, η2 = 0.002); LR defense of PBL, F(1, 228) = 0.19,
p = .661, η2 = 0.001; LR Total, F(1, 228) = 2.38, p = .124, η2 = 0.01)].
With respect to RQ2, differences were found between all the
groups, in all learning behaviors on the platform, except in access to
information on the oretical content. The differences in th e Bonferroni
test results for groups 4, 3, 2, and 1 were found in hierarchical
order from greater to lesser. With regard to access to guidelines to
conduct PBL, the differences were found in Group 3 on the others in
favor of this one (see Table 6). In relation to the covariable previous
knowledge, it no had no effect on any of the learning behaviors in
this analysis (Access to complementary information F(1, 228) = 0.60,
p = .44, η2 = 0.003; Access to the Guidelines for PBL F(1, 228) = 0.81,
p = .37, η2 = 0.004; Access to information on theoretical content F(1,
228) = 1.01, p = .32, η2 = 0.004; Access to teacher feedback, F(1, 228)
= 0.46, p = .50, η2 = 0.002; Mean number of visits per day, F(1, 228) =
1.61, p = .21, η2 = 0.01.
Subsequently, a xed-effects ANCOVA (type of B-Learning)
was applied to test RQ3, nding signi cant differences between
all the groups and under all the indicators of satisfaction with
teachers, except for the motivation of the teacher towards the
subject in which differences were only found between Groups 1
and 4. The highest measurements under satisfaction were found in
Group 3, a group in which infographs and virtual library resources
Differential efficacy of the resources used in B-learning environments
175
were administered (see Table 7). In this case, the co-variable
previous knowledge had no effects on any of the variables, Subject
matter F(1, 18 4) = 0.13, p = .72, η2 = 0.001; Continuous evaluation
F(1, 184) = 0.39, p = .53, η2 = 0.002; Teacher motivation F(1, 184) =
0.02, p = .88, η2 = 0.000; Workload F(1, 184) = 3.78, p = .05, η2 =
0.02; General satisfaction, F(1, 184) = 0.18, p = .67, η2 = 0.001.
Table 5
Single factor xed-effects ANOVA (Type of group) and value of the effect and test of mean differences between the Bonferroni groups for the variable learning results
LR
Group 1
n = 58
Group 2
n = 63
Group 3
n = 55
Group 4
n = 57
Single-factor ANOVA (type of
B-Learning) Bonferroni
by group
M SD M SD M SD M SD df F p η2
LR preparation of PBL
(Maximum score 2.50) 2.22 .18 2.19 .42 2.40 .37 2.72 .24 3,228 33.60 .000* 0.31
-.18* 1,3
-50* 1,4
-.21* 2,3
-.53* 2,4
-.32* 3,4
LR defense of the PBL
(Maximum score 2.50) 1.73 .29 1.76 .18 1.73 .18 1.64 .15 3,228 3.54 .015* 0.04 .12* 2,4
LR Quizzes
(Maximum score 3) 2.15 .42 2.59 .21 2.71 .14 2.72 .15 3,228 62.66 .000* 0.45
-.44* 1,2
-.56* 1,3
-.57* 1,4
-.12* 2,3
-.13* 2,4
LR Total
(Maximum score 10) 8.60 .72 9.05 .43 9.09 .49 8.15 1.15 3,228 19.95 .000* 0.21
-.45* 1,2
-.49* 1,3
.45* 1,4
.90* 2,4
.94* 3,4
* p <.05 Note. LR = Learning Results; M = Mean; SD = Standard Deviation; df = degrees of freedom; η2 = eta squared. Group 1 = Methodology B-Learning [20 (BL)-80% (F2F)]; Group 2 =
Methodology B-Learning [80 (BL)-20% (F2F)] + videos+ quizzes + product-oriented feedback; Group 3 = Methodology B-Learning [80 (BL)-20% (F2F)] + videos + quizzes + process-oriented
feedback + infographs + virtual laboratory; Group 4 = B-Learning [80 (BL)-20% (F2F)] methodology + videos + quizzes+ process-oriented feedback
Table 6
Single factor xed-effects ANOVA (Type of group) and effect value and test of i ntergroup different of means of Bonfer roni in the variables learning behavior on the
LMS
Access
Group 1
n = 58
Group 2
n = 63
Group 3
n = 55
Group 4
n = 57
Single-factor ANOVA (type of
B-Learning) Bonferroni
by group
M SD M SD M SD M SD df F p η2
Access to complementary 5.07 4.60 5.87 5.49 11.38 6.34 36.46 23.82 3,229 78.00 .00* 0.51
-31.39* 1,4
-30.58 2,4
-25.07 3,4
Access to orientations to be
done on the PBL 3.60 3.00 3.94 3.18 9.27 7.51 5.61 7.10 3,229 12.47 .00* 0.14
-5.67* 1,3
-5.34* 2,3
3.66* 3,4
Access to information on
theoretical content 13.81 7.49 13.64 7.35 14.56 10.83 14.63 8.12 3,229 .21 .89 0.003
Access to teacher feedback 18.43 21.14 25.44 33.18 90.47 28.40 114.28 46.13 3,229 117.37 .00* 0.61
-72.04* 1,3
-95.85* 1,4
-65.03* 2,3
-88.84* 2,4
-23.81* 3,4
Mean visits per day 1.08 .58 3.04 1.02 8.20 3.08 7.90 3.25 3,229 139.55 .00* 0.65
-1.96 1,2
-7.12 1,3
-6.821,4
-1.96 2,1
-5.16 2,3
-4.86 2,4
* p <.01 Note. M = Mean; SD = Standard Deviation; df = degrees of freedom; η2 = eta squared. Note. Group 1 = B-Learning [20 (BL)-80% (F2F)] methodology; Group 2 = B-Learning [80 (BL)-
20% (F2F)] methodology + videos+ quizzes + product-oriented feedback; Group 3 = B-Learning [80 (BL)-20% (F2F)] methodology + videos + quizzes + process-oriented feedback + infographs
+ virtual laboratory; Group 4 = B-Learning [80 (BL)-20% (F2F)] methodology + videos + quizzes+ process-oriented feedback
María Consuelo Sáiz Manzanares, César Ignacio García-Osorio, José Francisco Díez-Pastor
176
Discussion
It appears that the covariable previous knowledge in uenced
the learning results outcomes, particularly in the areas related with
the completion of individual tasks, but not for collaborative tasks.
Likewise, no incidents were observed in accessing the different
LMS resources, nor in satisfaction with the teaching activity. The
rst results coincided with those found by Taub & Azevedo (2019).
This conclusion is relevant to the design of activities in the LMS.
For example, collaborative tasks could be proposed between the
students in such a way that those with a higher level of previous
knowledge support the work of students with lower levels. In
addition, the Meta-Tutoring from the implementation of different
hyper-media resources appeared to compensate the effect of the
variable previous knowledge on the LR.
It was also found that the differences in the LR were not
homogeneous between the different evaluation procedures. For
example, better LR results were found in the preparation of the
PBL in Group 4, in which a B-Learning (80%/20%) methodology
was implemented with hypermedia resources of video displays
and post-video comprehension quizzes. However, for the Defense
of PBL, the best results were found in Group 2, in which a
B-Learning (80%-20%) methodology was applied, which included
videos with quizzes and process-oriented feedback. The patterns
of access were greater in groups 3 and 4, which implemented the
B-Learning (80%-20%) methodology with more sophisticated
hypermedia resources. To do so, it appears that the B-Learning
(80%-20%) design with more complex hypermedia resources
increased the activity of the students on the LMS. In addition, if
this environment included infographs and virtual laboratories,
there was a general increase in LR (Alves et al., 2016; Cerezo et
al., 2016; Gustavsson et al., 2009; Margulieux et al., 2016; Sáiz
et al., 2017; Viegas et al., 2018). One possible explanation is that
the combination of these resources strengthens the conceptual
comprehension of the student (Al-Dairy & Al-Rabaani, 2017)
and the personalization of learning (Kunze & Rutherford, 2018;
Harley et al., 2018), which facilitate the SRL and foreseeably the
use of metacognitive skills. All of which nally increase student
motivation (Zimmerman & Moylan, 2009).
Moreover, greater satisfaction was found with the teaching
activity in Group 3 which included t he use of infographs and virt ual
laboratories; a result that is agreement with those of Achuthan et
al. (2017), Haşlaman (2018), and Santos et al. (2019).
In summary, it appears that the design of the B-Learning spaces
in uences the LR and behavioral-learning patterns in the students.
However, there are other variables, such as previous knowledge
that could be exerting some in uence (Xi et al., 2018), especially
on the LR.
Nevertheless, the generalization of the results of this study
must be treated with prudence, attending to the characteristics of
the sample: number, origin, sampling, history of student learning,
speci city of quali cation and subject matter. Future investigations
will be directed towards establishing the ef cacy of B-Learning
(80%-20%) environments in other areas of knowledge, in which
different hypermedia resources are included.
Acknowledgements
This study was completed with grants from the Vice-Rectorate
of Teaching, Teaching Research and Research Staff of the
University of Burgos for teaching innovation 2019 awarded to the
B-learning Teaching Innovation Group in Health Sciences and
the Vice-Rectorate of Research and Knowledge Transfer 2019
awarded to support research groups recognized for DATAHES.
The suggestions of the reviewers have also served to improve the
quality of this document.
Table 7
Indicators of Student Satisfaction with t he quality of teaching [Bol et al. (2013) adapted from Marsh (1987)]
Satisfaction
Group 1
n = 31
Response rate
53.44
Group 2
n = 51
Response rate
80.95
Group 3
n = 53
Response rate
96.36
Group 4
n = 54
Response
rate
94.74
Single-factor ANOVA (type of
B-Learning) Bonferroni
by group
M SD M SD M SD M SD df F p η2
Materials 4.11 .74 4.29 .64 4.56 .53 3.79 .89 3,185 10.82 .00* 0.15
-.44* 1,3
.50 2,4
.77 3,4
Continuous evaluation 3.79 .93 4.23 .75 4.55 .64 3.46 .97 3,185 17.25 .00* 0.22
-.76* 1,3
-.76* 2,4
1.08* 3,4
Motivation of teacher 4.37 .75 4.40 .68 4.64 .40 3.75 .93 3,185 14.87 .00* 0.19
.62* 1,4
.65* 2,4
.88*3,4
Workload 4.23 .80 3.84 .67 4.02 .82 3.65 .93 3,185 3.81 .01* 0.06 -.58* 1,4
General satisfaction 4.13 .67 4.31 .55 4.58 .42 3.69 .82 3,185 18.90 .00* 0.24
-.46* 1,3
.44* 1,4
.62* 2,4
.89* 3,4
* p <.01 Note. M = Mean; SD = Standard Deviation; df = degrees of freedom; η2 = eta squared
Differential efficacy of the resources used in B-learning environments
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... It has been proven that with these techniques, the prediction percentage is in the range of 79-83% [11]. Additionally, it has been found that the use of teaching methodology in virtual environments based on self-regulated learning (SRL) [12] together with project-based learning (PBL) [13,14] and the use of continuous assessment methodology [15] are predictors of the achievement of effective learning (60.4%) [16] and decrease the dropout rate [15,17]. In summary, these studies indicate that one of the ways to decrease the percentage of students who drop out of university is to have systems in the LMS that facilitate the detection of the student at risk throughout the teaching-learning process [18,19]. ...
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In this study, we used a module for monitoring and detecting students at risk of dropping out. We worked with a sample of 49 third-year students in a Health Science degree during a lockdown caused by COVID-19. Three follow-ups were carried out over a semester: an initial one, an intermediate one and a final one with the UBUMonitor tool. This tool is a desktop application executed on the client, implemented with Java, and with a graphic interface developed in JavaFX. The application connects to the selected Moodle server, through the web services and the REST API provided by the server. UBUMonitor includes, among others, modules for log visualisation, risk of dropping out, and clustering. The visualisation techniques of boxplots and heat maps and the cluster analysis module (k-means ++, fuzzy k-means and Density-based spatial clustering of applications with noise (DBSCAN) were used to monitor the students. A teaching methodology based on project-based learning (PBL), self-regulated learning (SRL) and continuous assessment was also used. The results indicate that the use of this methodology together with early detection and personalised intervention in the initial follow-up of students achieved a drop-out rate of less than 7% and an overall level of student satisfaction with the teaching and learning process of 4.56 out of 5.
... Likewise, it was confirmed that the teaching style appears to condition student behavior on the LMS, which supports what has been found in other investigations [1,2,[8][9][10][11][12]. This aspect sheds light on the frequency of use of resources and activities, suggesting that it depends on the instructional design that the teacher implements. ...
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Teaching in Higher Education is with increasing frequency completed within a Learning Management System (LMS) environment in the Blended Learning modality. The use of learning objects (activities and resources) offered by LMS means that both teachers and students require training. In addition, gender differences relating to the number of students in STEM (Science, Technology, Engineering, and Mathematics) and Non-STEM courses might have some influence on the use of those learning objects. The study involves 13 teachers (6 experts in e-Learning and 7 non-experts) on 13 academic courses (4 STEM and 9 Non-STEM) and a detailed examination of the logs of 626 students downloaded from the Moodle platform. Our objectives are: (1) To confirm whether significant differences may be found in relation to the use of learning objects (resources and activities) on Moodle, depending on the expertise of the teacher (expert vs. non-expert in e-Learning); (2) To confirm whether there are significant differences between students regarding their use of learning objects, depending on the expertise of the teacher (expert vs. non-expert in e-Learning); (3) To confirm whether there are significant differences for the use of learning objects among students as a function of gender. Differences were found in the use of Moodle learning objects (resources and activities) for teachers and for students depending on the expertise of the teacher. Likewise, differences were found for the use of some learning objects as a function of gender and the degrees that the students were following. Increased technological training for both teachers and students is proposed, especially on Non-STEM qualifications, in order to mitigate the effects of the technological gap and its collateral relation with the gender gap and the digital divide.
... Previous studies in different disciplines have examined the implementation of blended learning and its potential benefits for learning (see Bergmann & Sams, 2012;Brent et al., 2002;Davies et al., 2013;Lage et al., 2000;Sáiz et al., 2020aSáiz et al., , 2020bSáiz et al., 2019aSáiz et al., , 2019b. Stone (2012) flipped two courses, genetic diseases and general biology. ...
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Learning management systems (LMSs) that incorporate hypermedia Smart Tutoring Systems and personalized student feedback can increase self-regulated learning (SRL), motivation, and effective learning. These systems are studied with the following aims: (1) to verify whether the use of LMS with hypermedia Smart Tutoring Systems improves student learning outcomes; (2) to verify whether the learning outcomes will be grouped into performance clusters (Satisfactory, Good, and Excellent); and (3) to verify whether those clusters will group together the different learning outcomes assessed in four different evaluation procedures. Use of the LMS with hypermedia Smart Tutoring Systems was studied among students of Health Sciences, all of whom had similar test results in the use of metacognitive skills. It explained 38% of the variance in student learning outcomes in the evaluation procedures. Likewise, three clusters that grouped the learning outcomes in relation to the variable ‘Use of an LMS with hypermedia Smart Tutoring Systems vs. No use’ explained 60.4% of the variance. Each cluster grouped the learning outcomes in the different evaluation procedures. In conclusion, LMS with hypermedia Smart Tutoring Systems in Moodle increased the effectiveness of student learning outcomes, above all in the individual quiz-type tests. It also facilitated personalized learning and respect for the individual pace of student-learning. Hence, modules for the analysis of supervised, unsupervised and multivariate learning should be incorporated into the Moodle platform to provide teaching tools that will undoubtedly contribute to improvements in student learning outcomes. HIGHLIGHTS-Learning management systems (LMS) that incorporate hypermedia Smart Tutoring Systems and personalized student feedback can increase self-regulated learning (SRL). -Learning management systems with hypermedia Smart Tutoring Systems increased the effectiveness of student learning outcome. -The use of an LMS with hypermedia Smart Tutoring Systems vs. No use’ explained 60.4% of the variance in student learning outcome.
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