Towards Deep Learning in the University through Collaborative
Instructional Design based on Learning Outcomes and Threshold
Concepts
Jack Fernando Bravo-Torres
1,2 a
, Mar
´
ıa Dolores Fern
´
andez P
´
erez
1 b
,
Cinthya Mar
´
ıa Cevallos-Lude
˜
na
3 c
, Wilson Daniel Bravo-Torres
4 d
and Esteban Fernando Ordo
˜
nez-Morales
2 e
1
Escuela Internacional de Doctorado, Doctorado en Educaci
´
on, Universidad Nacional de Educaci
´
on a Distancia,
Madrid, Spain
2
Grupo de Investigaci
´
on en Telecomunicaciones y Telem
´
atica (GITEL), Universidad Polit
´
ecnica Salesiana del Ecuador,
Cuenca, Ecuador
3
Facultad de Filosof
´
ıa, Letras y Ciencias de la Educaci
´
on, Universidad de Cuenca, Cuenca, Ecuador
4
Grupo de Investigaci
´
on en Rehabilitaci
´
on Oral (GIRO), Universidad de Cuenca, Cuenca, Ecuador
Keywords:
Collaborative Teaching, Learning Outcomes, Threshold Concepts, Teacher Cloisters, Conceptual Structure of
Knowledge.
Abstract:
This article presents a proposal for the development of a collaborative curriculum and instructional design
at the university. It starts from the premise that teaching-learning processes at any level of training must be
designed, managed and implemented in a collaborative way, supported by teacher structures grouped around
their domains of knowledge. Moreover, we consider as central axes of all curricular and instructional design
a correct selection and structuring of the contents to be studied, based on the identification of the conceptual
structures of the topics under study (threshold concepts and their interlinkages) together with an appropriate
definition of the desired learning outcomes and evaluation tools.
1 INTRODUCTION
Today’s society is characterized by the preponderance
that information and knowledge have taken in the gen-
eration of wealth and in the very development of so-
cial and economic life (North et al., 2018). This has
been favored by advances in information and com-
munication technologies, mobile systems, microelec-
tronics, and greater storage capabilities, processing
and access to data almost ubiquitously. This tech-
nological evolution leads us to a potentialization of
the world of work, allowing the execution of more
complex tasks and the automation of routine pro-
cesses. This reality leads people and organizations
to carry out their activities in an environment of
a
https://orcid.org/0000-0001-9994-6063
b
https://orcid.org/0000-0001-5026-8660
c
https://orcid.org/0000-0001-8331-5443
d
https://orcid.org/0000-0002-9431-1808
e
https://orcid.org/0000-0002-2000-5883
high volatility, uncertainty, complexity and ambigu-
ity (Bongiorno et al., 2018), which in turn implies a
change in the structure and future of work (Steiner,
2020). Thus, greater competitive advantage is given
to those with the ability to learn (Rimbau, 2013) and
skills for creativity, innovation, imagination and de-
sign (Brown et al., 2017): the so-called knowledge
workers.
As can be seen, this new social situation creates
a series of challenges for workers and for their train-
ing (North et al., 2018). We need professionals with
a deep understanding of the main concepts that struc-
ture their disciplines, enabling them to act on the basis
of that knowledge, moving from knowledge to com-
petence, and from competence to action; with a train-
ing that allows them to be aware of the complexity of
the environment, and of learning as a means to deal
with it. From this perspective, it is clear that contem-
porary society is affecting the university, as a social
organization, in all its organizational structure, pro-
cesses and in the organizational culture itself. On the
Bravo-Torres, J., Fernández Pérez, M., Cevallos-Ludeña, C., Bravo-Torres, W. and Ordoñez-Morales, E.
Towards Deep Learning in the University through Collaborative Instr uctional Design based on Learning Outcomes and Threshold Concepts.
DOI: 10.5220/0011092200003182
In Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022) - Volume 2, pages 543-548
ISBN: 978-989-758-562-3; ISSN: 2184-5026
Copyright
c
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
543
one hand, the training requirements of students and
professionals have changed drastically, but, above all,
they are highly dynamic. For example, in the field
of engineering, especially those related to electronics,
telecommunications and computing, the rate of tech-
nological change is such that it is impossible to cover
it completely during a four-year training period (Kay-
nak and Sait, 2020).
In this same environment of uncertainty, univer-
sity teaching must change in order to adjust and an-
ticipate the needs of those who are not just students,
but extend to society as a whole and its institutions.
Teachers are committed to developing skills for in-
teraction and knowledge generation in a distributed
way, based on networking, and with local and global
collaborative groups; which, in turn, involves extend-
ing their skills to manage diversity; and, finally, the
capacity for constant learning and innovation (North
et al., 2018). Similarly, as teachers, we face, from
the educational point of view, generations of stu-
dents with characteristics not seen in previous peri-
ods (Moore et al., 2017) and that lead to teaching and
learning being rethought. We are facing students ac-
customed to immediacy in information and results;
with technology as an environment of natural interac-
tion, and without the ability to approach information
in depth (Beamish, 2016).
Thus, in recent years, there has been a great inter-
est in the academic community for a series of method-
ological strategies to enrich teaching processes in the
field of science and engineering to stimulate students’
deep learning (Graham, 2018; Finelli and Froyd,
2019). Within this background of research, based on
the recommendations made by the American Society
of Engineering Education, in conjunction with other
organizations, three critical areas are proposed that
should be addressed (Finelli and Froyd, 2019): (i) im-
prove student learning in undergraduate engineering
education, (ii) improve and diversify the paths of en-
gineering students to increase retention, and (iii) use
technology to improve learning, and participation and
commitment in engineering.
Our interest is mainly focused on generating con-
tributions in the first critical area. So, starting from the
question, who and what should we change in our work
to improve learning in undergraduate engineering ed-
ucation?, (Finelli and Froyd, 2019) propose four di-
rections for action: (i) change of organizational cul-
ture, (ii) research into effective evaluation practices,
(iii) promote the adoption of research-based teach-
ing practices, and (iv) characterize the development
of successful faculties. In this sense, these authors
show that in the literature there is a large set of re-
search (Umbach, 2007; Elrod and Kezar, 2017) that
relates the decisions and practices of instruction and
evaluation with aspects of the organization (depart-
ments, faculties, association of teachers): teachers
tend to generate a common practice. This aspect is
shown as an important point, and even a barrier to
overcome, when generating changes in higher educa-
tion. Thus, in accordance with this vision, this work,
in the first instance, seeks to analyze a new form of
organizational structure, the so-called ”teacher clois-
ter”, as a central axis in the deployment of strategies
for the promotion of students’ deep learning.
Regarding research on effective evaluation prac-
tices, several studies show the importance of for-
mative evaluation (Irons, 2007; McTighe and Wig-
gins, 2012; Qadir et al., 2020), feedback (Limniou
and Smith, 2014; McConlogue, 2020) and remedi-
ation (Karpicke, 2017) as strategies to improve stu-
dent learning. However, it is clear that the desired
learning outcomes need to be articulated so that they
are clearly known by students (Finelli and Froyd,
2019) and that, in addition, those outcomes to guide
the entire learning process (Biggs and Collis, 2014).
This step is fundamental and must be supported by
a wide range of professionals who define these out-
comes (Finelli and Froyd, 2019). In line with the
above, appropriate tasks and assessment tools should
be designed so that students can demonstrate the ex-
tent of the proposed outcomes. In this sense, our pro-
posal shares the criteria of (Biggs and Collis, 2014)
and (McTighe and Wiggins, 2012) regarding the cen-
trality of evaluation to improve the performance and
learning of students; but, we consider it transcendent
that, in addition to the evaluation criteria and instru-
ments, the instructional design must be based on a
structuring of knowledge, based on the threshold con-
cepts of each discipline and its relationships.
In this context, the organizational structure of the
university, in particular the organisation of teaching
staff, and instructional design for the training of fu-
ture professionals should be rethought to provide an
education that enables students to achieve deep learn-
ing and the skills needed to manage complexity and
uncertainty; while implementing a collaborative and
transdisciplinary teaching and learning process. That
is, the teaching process cannot be seen as an indi-
vidual activity of each teacher, disconnected from the
activity of the other teachers of the degree; but must
be assumed as a collective action. From our point of
view, an instructional design based on results-based
pedagogical actions (Biggs, 2011; Biggs and Collis,
2014) and on threshold concepts (Stern et al., 2017),
and supported by a teaching structure that stimulates
joint instructional design and collaborative teaching
can enhance deep learning (Biggs and Collis, 2014)
of university students.
This article is organized as follows. In Section II,
CSEDU 2022 - 14th International Conference on Computer Supported Education
544
we present the main foundations that support our pro-
posal of instructional design and collaborative teach-
ing, focusing on the conceptualization of ”teacher
cloisters” and pedagogical proposals based on learn-
ing outcomes and threshold concepts. Then, in Sec-
tion III, we briefly describe the interactions that are
presented in curriculum design between teachers and
students. Finally, Section IV concludes the paper and
points out some lines of future work.
2 BACKGROUND
As discussed in the previous section, our instructional
design proposal is based on two key aspects: (i) a col-
laborative teaching process through the organization
of teachers’ work in the so-called ”teacher cloisters”
and (ii) the structuring of knowledge and the design
of the teaching and learning process based on learning
outcomes and threshold concepts. In this section, we
will address the main features of these two aspects.
2.1 Areas of Knowledge and Teacher
Cloisters
In general, areas of knowledge can be seen as a way to
organize the university’s teaching staff. For example,
in the case of the Salesian Polytechnic University of
Ecuador (UPS), where this vision was implemented,
previously, teaching staff gathered around careers and
faculties, but this distribution generated a partial view
of knowledge; In addition, it was intended to gener-
ate rivalries between faculties, a sense of belonging
to the faculty and not to the university, as well as an
underutilization of teaching resources and capacities.
In this context, the idea of areas of knowledge is the
grouping of teachers not by faculties but by the area of
science in which they specialize. In this way, the hu-
man capital of the university can serve all the careers
and/or projects that are generated (research, curric-
ula, postgraduate, etc.). It should also be noted that
the multidisciplinary and transdisciplinary nature is
directly present in the project under implementation,
which does not represent a faculty but the university,
and in which the professors will intervene from the
multiple areas.
Within these macro structures of educational or-
ganization, teachers are subdivided into teacher clois-
ters, made up of those teachers who belong to a spe-
cific domain of knowledge within the broad field of
the area. In turn, these cloisters incorporate research
groups and/or educational innovation groups. For ex-
ample, again, with regard to UPS, the Teacher Clois-
ter of Telecommunications brings together the Re-
search Group on Telecommunications and Telemat-
ics (GITEL), with its lines of research: telemedicine,
e-learning, e-agriculture, optical communications,
wireless communications; and the Group on Edu-
cational Innovation in Telecommunications (GIET),
with its lines of innovation and action: design of
learning methodologies, generation of teaching mate-
rials, shared evaluation methodologies, evaluation of
teaching actions, coordination of subjects associated
with their field of study (this allows the cloisters to
relate to the undergraduate and postgraduate careers
that require their services).
Note at this point that the management of teaching
and learning supported by the cloisters allows teach-
ers to find a natural space for their research activi-
ties within research groups and for innovation in their
teaching, through educational innovation groups. Of
course, for this to make sense, there is a coordina-
tion structure between the faculty and the directors of
the innovation and research groups. This allows di-
rect interrelationships between innovative educational
and research processes to be generated, and students
can be involved in the research carried out by these
groups, since they are invited to participate in ad hoc
research projects, with which research and teaching
are interrelated and support the learning of students.
2.2 Learning Outcomes and Threshold
Concepts in Instructional Design
In the development of university teaching, and in gen-
eral of any of the levels of formation, one of the fun-
damental tasks corresponds to the instructional de-
sign of the courses to be imparted. This activity is
key to student learning because it clearly defines the
learning objectives and the processes, tools and ma-
terials that will be applied to achieve them. More-
over, our choices in design will be the result of the
different conceptions, conscious or unconscious, that
we possess about what teaching means. This also ap-
plies to our and the students’ understanding of learn-
ing (Biggs, 2011). For example, from a superficial
view of learning students intend to execute their tasks
with minimal effort, with the apparent view that they
meet the requirements of the course. This also leads
to students using low-level cognitive abilities, rather
than high-level ones when they are required. How-
ever, this way of conceiving learning is closely linked
to the teaching process. From a superficial perspec-
tive, teaching is seen as the delivery of content in the
form of lists, without showing an intrinsic structure
of the topics; with evaluations focused, in the same
way, on independent facts. On the contrary, a deep
approach to learning presents students who seek to
Towards Deep Learning in the University through Collaborative Instructional Design based on Learning Outcomes and Threshold Concepts
545
meaningfully appropriate tasks, with a conceptual, re-
lational and structural approach to the topics under
study. This action is stimulated by the teaching work
that develops an approach to knowledge from a struc-
tural vision, with the purpose of an active learning,
with evaluation as a form of positive stimulation of
that learning (Biggs, 2011; Biggs, 2014; Biggs and
Collis, 2014).
From the perspective of students’ deep learning,
one of the proposals in the literature is the so-called
aligned constructivism (Biggs, 2014) that mixes a
constructivist approach—with the idea that the ap-
prentice builds his knowledge from the interpreta-
tions he develops from his pre-existing schemes—
and alignment—as a principle of curriculum theory
that states that assessment tasks are aligned with what
is intended to be learned—. In this proposal, the
expected results specify the activity that the student
must develop if he or she wishes to achieve the desired
result together with the content to which that activity
refers, how it should be learned and under what stan-
dard it will be evaluated. The underlying idea is that
if the student knows how he or she will be evaluated
and with what quality he or she is expected to develop
that activity, the students will tend to reach that level,
which can be profound, depending on the teacher’s
perspectives (Biggs, 2011). An idea similar to that
of aligned constructivism, although with variations in
how to conceive of evaluation as a tool to test learning
rather than as part of the teaching and learning pro-
cess, is the backward design (Wiggins et al., 2005).
Here, the first step of the design is the identification
of the desired results, followed by the determination
of acceptable evidence (evaluation) to finish with the
learning and instructional experiences. As we can see,
in both cases, the learning results and the evaluation
are the key points of the instructional design on which
the other instances of planning are articulated.
A different conceptualization of the instructional
design process is that in which the contents are fun-
damental when designing the teaching and learning
process. From this perspective, for example, concept-
based curriculum design (Stern et al., 2017) tells us
that abstraction at the conceptual level is fundamen-
tal to understanding problems and creating solutions.
That is, independent facts do not allow a proper trans-
fer to other contexts. In this sense, traditional curricu-
lum models based on content coverage rarely produce
deep and transferable learning (Stern et al., 2017;
Burch et al., 2015). And this is even more dramatic
when we focus on the area of engineering, especially
communication technologies, where the rate of tech-
nological change is extremely high. In this context,
it is necessary to promote formative processes that
allow the development of synergistic thinking where
there is a cognitive interrelation between low and con-
ceptual levels according to the needs of individuals.
Therefore, it is essential to establish the contents to
be taught, but from a structuring of knowledge based
on concepts and their relationships, not simply as lists
of topics to be addressed. From this same perspec-
tive, the determination of threshold concepts (Meyer
and Land, 2006; Burch et al., 2015)—defined as those
concepts that allow students to open their thinking to a
new and broader form of understanding of some topic,
which could not be accessible without their study—
together with the identification of those troublesome
concepts—concepts of wide complexity for students
due to their level of abstraction or their requirements
of mastery of previous knowledge— are fundamental
to the time of establish such a conceptual structure to
enable the approach, deep understanding and subse-
quent transfer to new contexts.
In general, our view is that, in instructional design,
learning outcomes and assessment processes along
with the knowledge structure based on threshold con-
cepts are central to pursuing deep learning, allowing
the harmonisation of all elements of the teaching and
learning process. However, it is necessary to change
the vision of teaching as an individual action of teach-
ers towards a new structure of design, planning and
execution of a collaborative teaching, supported by
the formation of academic cloisters. In the next sec-
tion, we present a first proposal that allows us to ap-
proach this type of collaborative design.
3 TOWARDS A
COLLABORATIVE
INSTRUCTIONAL DESIGN
FOCUSED on CONCEPTUAL
STRUCTURE AND LEARNING
OUTCOMES
As mentioned in the preceding sections, this proposal
is based on a principle of collaborative teaching, sup-
ported by teacher cloisters. Figure 1 shows the differ-
ent stages of the teaching and learning process, and
interrelations that are generated between the teachers
of the cloister. The design phase corresponds to the
instructional design of the subject, which is an activ-
ity that is executed among the teachers belonging to
the domain in which this subject is inserted. That is,
this whole process is not developed individually by
the teacher who dictates this subject, but he coordi-
nates a working group that is responsible for the en-
tire design process, which includes the structuring of
CSEDU 2022 - 14th International Conference on Computer Supported Education
546
contents, the desired learning standards, the evalua-
tion tools and the experiences and learning resources
needed to achieve the desired results. In a second
phase, the proposed design is put into effect; this ac-
tivity is individual (or group, according to the teach-
ing modality of the university) and is implemented
by the professor in charge of the subject and/or his
collaborators. A third stage, which develops as the
proposal is implemented, corresponds to the control
and feedback stage. In it, again, the teacher cloister,
specifically the teachers of the corresponding domain,
analyze the preliminary and/or final data, as appropri-
ate, of the evaluation and assessment processes de-
signed, in order to take the necessary corrective mea-
sures during implementation and to improve the ini-
tial design.
Control and
feedback
(Teacher Cloisters)
Design
(Teacher Cloisters)
Implementation
(Teacher)
Figure 1: Phases of the teaching and learning process, and
its relationship with the teacher cloisters.
With respect to instructional design it rests on a
fully interactive multilayer architecture, which im-
plies a cross-layer structure, so that the information
provided from the various layers can be used by the
others in the design process. Conceptually, this archi-
tecture has five layers or levels (see Figure 2) that will
be described in the following subsections.
Level of Conceptual Structure
This level of the instructional design process will
identify the different threshold concepts and problem
concepts associated with the topic of study, as well
as the relationships that are generated between them
and with the previous knowledge that students must
possess to be able to face them. The expected result
is the conceptual structure of the knowledge that will
be addressed throughout the course, and prioritizing a
structure based on threshold concepts. For the devel-
opment of this level is expected the joint work of the
teachers of the domain, experts in these topics, and, if
possible, the participation of students who have stud-
ied this subject, to detect the problematic concepts
Learning Experiences
and
Instruction
Evaluation and Assessment
Desired Learning Outcomes
Conceptual Structure
Figure 2: Architecture of the instructional design process
focused on a conceptual structure and learning outcomes.
and their motivations.
Level of Desired Learning Outcomes
Following the proposal of (Biggs and Collis, 2014), at
this level, our intention is that both teachers and stu-
dents be aware of the different levels of understanding
required in the course, for each of the aspects stud-
ied. To this end, at this level, the teaching team will
propose the desired learning results, which must be
achieved after the teaching process and must clearly
specify what to do and under what standards the stu-
dent will demonstrate these achievements.
Level of Evaluation and Assessment
At this point, following the perspective of the back-
ward design proposed by (Wiggins et al., 2005), it is
necessary to determine how we will recognize that the
student has achieved the desired result? That is, at this
level, teachers will design assessment and evaluation
activities and instruments that will allow feedback
on the student’s learning process and the teacher’s
teaching process and also, generate the correspond-
ing scores for your accreditation. The design perspec-
tive that is prioritized is that the evaluation activities
are part of the teaching process and therefore must be
structured so that the student can deepen his learning
from them, more than obtain a score and the accredi-
tation of the achievement of the desired results.
Level of Learning and Instructional Experiences
Finally, with all the information obtained at the pre-
vious levels, it corresponds to this point the design of
different learning experiences and instruction so that
Towards Deep Learning in the University through Collaborative Instructional Design based on Learning Outcomes and Threshold Concepts
547
students reach the desired levels of understanding. At
this level of design, according to the proposed degrees
of comprehension, the established knowledge struc-
ture, the area of knowledge and the evaluation instru-
ments developed, teachers will establish methodolo-
gies, activities and teaching resources needed to sys-
tematically provide students with experiences that en-
able them to achieve the desired level of performance.
As can be seen, this instructional design proposal
is based on the conceptual structure of knowledge and
evaluation as essential aspects in the harmonization of
the teaching and learning process, for the achievement
of deep learning in university students.
4 CONCLUSIONS
In this article we have presented the conceptual de-
scription of a proposal of instructional design at uni-
versity level that, unlike other proposals present in
the literature, is based on the collaborative action of
teachers belonging to a domain of knowledge within
a teacher cloister. To this end, the conceptual struc-
ture of knowledge to be taught is defined as central
and harmonizing aspects of the teaching and learn-
ing process (threshold and troublesome concepts) and
the clear definition of the desired learning outcomes
together with the tools for assessing and evaluating
those outcomes. Our intention is to test this proposal
through the Teacher Cloisters of Telecommunications
of the Salesian Polytechnic University of Ecuador, in
the area of mobile and wireless communications, in
the Career of Telecommunications Engineering.
REFERENCES
Beamish, R. (2016). The Promise of Sociology: Classical
Approaches to Contemporary Society. University of
Toronto Press.
Biggs, J. (2014). Constructive alignment. HERDSA Review
of Higher Education, 1:25.
Biggs, J. B. (2011). Teaching for quality learning at univer-
sity: What the student does. McGraw-hill education
(UK).
Biggs, J. B. and Collis, K. F. (2014). Evaluating the qual-
ity of learning: The SOLO taxonomy (Structure of the
Observed Learning Outcome). Academic Press.
Bongiorno, G., Rizzo, D., and Vaia, G. (2018). Cios and the
digital transformation: a new leadership role. In CIOs
and the digital transformation, pages 1–9. Springer.
Brown, J., Gosling, T., Sethi, B., Sheppard, B., Stubbings,
C., Sviokla, J., and Zarubina, D. (2017). Workforce of
the future: The competing forces shaping 2030. Lon-
don: PWC.
Burch, G. F., Burch, J. J., Bradley, T. P., and Heller,
N. A. (2015). Identifying and overcoming threshold
concepts and conceptions: Introducing a conception-
focused curriculum to course design. Journal of Man-
agement Education, 39(4):476–496.
Elrod, S. and Kezar, A. (2017). Increasing student success
in stem: Summary of a guide to systemic institutional
change. Change: The Magazine of Higher Learning,
49(4):26–34.
Finelli, C. J. and Froyd, J. E. (2019). Improving student
learning in undergraduate engineering education by
improving teaching and assessment. Advances in En-
gineering Education.
Graham, R. (2018). The global state of the art in engineer-
ing education. Massachusetts Institute of Technology
(MIT) Report, Massachusetts, USA.
Irons, A. (2007). Enhancing learning through formative
assessment and feedback. Routledge.
Karpicke, J. D. (2017). Retrieval-based learning: A decade
of progress. Grantee Submission.
Kaynak, O. and Sait, S. M. (2020). Engineering education
at the age of digital transformation.
Limniou, M. and Smith, M. (2014). The role of feedback in
e-assessments for engineering education. Education
and Information Technologies, 19(1):209–225.
McConlogue, T. (2020). Assessment and feedback in higher
education: A guide for teachers.
McTighe, J. and Wiggins, G. (2012). Understanding by de-
sign framework. Alexandria, VA: Association for Su-
pervision and Curriculum Development.
Meyer, J. H. and Land, R. (2006). Threshold concepts and
troublesome knowledge: An introduction. In Over-
coming barriers to student understanding, pages 27–
42. Routledge.
Moore, K., Frazier, R. S., et al. (2017). Engineering educa-
tion for generation z. American Journal of Engineer-
ing Education (AJEE), 8(2):111–126.
North, K., Maier, R., and Haas, O. (2018). Value cre-
ation in the digitally enabled knowledge economy. In
Knowledge Management in Digital Change, pages 1–
29. Springer.
Qadir, J., Taha, A.-E. M., Yau, K.-L. A., Ponciano, J., Hus-
sain, S., Al-Fuqaha, A., and Imran, M. A. (2020).
Leveraging the force of formative assessment & feed-
back for effective engineering education.
Rimbau, G., E. (2013). La direcci
´
on de persones en la so-
ciedad del conocimiento. Technical report, Universi-
dad Oberta de Catalu
˜
na.
Steiner, O. (2020). Social work in the digital era: Theoret-
ical, ethical and practical considerations. The British
Journal of Social Work.
Stern, J., Ferraro, K., and Mohnkern, J. (2017). Tools for
teaching conceptual understanding, secondary: De-
signing lessons and assessments for deep learning.
Corwin Press.
Umbach, P. D. (2007). Faculty Cultures and College Teach-
ing, pages 263–317. Springer Netherlands, Dordrecht.
Wiggins, G. P., Wiggins, G., and McTighe, J. (2005). Un-
derstanding by design. Ascd.
CSEDU 2022 - 14th International Conference on Computer Supported Education
548