Assessment of Generic Skills through an Organizational Learning
Process Model
Antonio Balderas
, Juan Antonio Caballero-Hern
, Juan Manuel Dodero
Manuel Palomo-Duarte
and Iv
an Ruiz-Rube
Department of Computer Science, Universidad de C
adiz, Av. de la Universidad de C
adiz 10, Puerto Real, Spain
EVAL for Research Group, Universidad de C
adiz, Av. Rep
Arabe Saharaui s/n, Puerto Real, Spain
Knowledge Management System, Life-Long Learning, Generic Skills Assessment, Learning Management
System, Learning Analytics, Model-driven Architecture, REST Web Service.
The performance in generic skills is increasingly important for organizations to succeed in the current com-
petitive environment. However, assessing the level of performance in generic skills of the members of an
organization is a challenging task, subject to both subjectivity and scalability issues. Organizations usually
lay their organizational learning processes on a Knowledge Management System (KMS). This work presents a
process model to support managers of KMSs in the assessment of their individuals’ generic skills. The process
model was deployed through an extended version of a learning management system. It was connected with
different information system tools specifically developed to enrich its features. A case study with Compu-
ter Science final-year students working in a software system was conducted following an authentic learning
approach, showing promising results.
Lifelong Learning is generally defined as the educa-
tional activities that individuals have been involved
during their lives (Ozdamli and Ozdal, 2015), invol-
ving learning experiences that take place at home, in
the workplace, in universities and colleges, and in ot-
her educational, social, and cultural agencies, institu-
tions, and settings, both formal and informal (Aspin
and Chapman, 2007). Lifelong Learning in the work-
place is a key factor for the success of companies,
since today’s competitive environment requires pro-
fessionals in any field to continuously improve their
skills in order to face new challenges in their area of
knowledge (Gagnon et al., 2015; Hennekam and Ben-
nett, 2017).
In this context, the demand of employees on com-
panies has shifted its focus from knowledge to skills
(Crebert et al., 2004). Competencies can be divi-
ded into subject-specific and generic (Andrews and
Higson, 2008). While subject specific competencies
are related to knowledge in the subject areas, ge-
neric competencies are the abilities, capacities and
knowledge that any person should develop regard-
less of his/her subject area. Generic skills compe-
tence is relevant for organizations, and future gradua-
tes are preparing at universities to meet labour market
needs (Fit
o-Bertran et al., 2015; Edwards-Schachter
et al., 2015). As a result, the strategic management
has to focus on the internal capabilities of organizati-
ons in order to strategically align its human resources
with employee capabilities (Svetlik et al., 2007; Hu-
ang et al., 2016). In organizations, generic skills such
as leadership or teamwork are usually key to consider
the most suitable candidate for a position (Nita et al.,
2016). However, objectively determining the level of
performance in generic skills of every member of an
organization is a challenging task. This work beco-
mes even more demanding for large-sized organizati-
ons, where the number of workers interacting can be
really high.
The competence of an organization can be enhan-
ced adding organizational learning to the relations-
hip between knowledge transfer and dynamic com-
petence (Huang and Guo, 2010). Organizational le-
arning is the process by which an organization incre-
ases the knowledge created by individuals in an or-
ganized way and transforms this knowledge into part
of the knowledge organization system. The process
takes place at an individual level, at a group level
and at a system organization level (Reese and Hunter,
2016), having a positive influence both organizational
Balderas, A., Caballero-Hernández, J., Dodero, J., Palomo-Duarte, M. and Ruiz-Rube, I.
Assessment of Generic Skills through an Organizational Learning Process Model.
DOI: 10.5220/0006960802930300
In Proceedings of the 14th International Conference on Web Information Systems and Technologies (WEBIST 2018), pages 293-300
ISBN: 978-989-758-324-7
Copyright © 2018 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
performance and organizational innovation (Garc
Morales et al., 2012).
To support organizational learning, medium or
large size organizations usually rely on a Knowledge
Management System (KMS). KMSs provide organi-
zations with different advantages in terms of com-
munication, learning, sharing information, informa-
tion retrieval and learning functions integration (Lie-
bowitz and Frank, 2016). Unfortunately, KMSs do
not usually provide managers with objective indica-
tors about the generic skills performance of their in-
dividuals (i.e. staff).
A Learning Management System (LMS) is a web-
based virtual educational environment with different
modules to support learning processes. LMSs are
commonly used in educational centres at all levels and
can also be considered as KMS tools (Abu Shawar
and Al-Sadi, 2010). In a LMS, supervisor can ana-
lyze learning situations by collecting interaction re-
cords produced by these environments (Chebil et al.,
2012; Fidalgo-Blanco et al., 2015b).
Thus, can learning records in a KMS be used as
evidences to automate the assessment process of in-
dividuals’ performance in generic skills? This paper
proposes a process model ultimately aimed at asses-
sing the acquisition of certain skills by using a KMS
built on top of a LMS and a set of dedicated tools
published under open-source license. This process
and these tools facilitate both the manual assessment
of generic skills linked to evidences and the automa-
tic extraction of objective indicators for those skills.
To test the process model, a case study assessing se-
veral generic skills of individuals is conducted, sho-
wing promising results.
The rest of the paper is organized as follows:
Section 2 reviews the background. Section 3 intro-
duces the proposed process. Section 4 presents the
set of tools implemented. Section 5 describes a case
study about the assessment of several generic skills
through an authentic learning experience. Finally, in
the last section, we provide a discussion along with
conclusions and future research lines.
In the current competitive context, knowledge mana-
gement process within organizations aims to enhance
both their individuals and group skills. Some generic
skills, such as teamwork or planning and time mana-
gement, are fundamental for individuals’ job perfor-
mance and, consequently, the successes of the organi-
zation (Ahmad et al., 2012; Burt et al., 2010).
Thus, this knowledge management process is usu-
ally embedded in virtual learning frameworks. A
study focused on building students’ engagement in
virtual courses demonstrated that the main reason for
the high withdrawal rate was the participants’ poor
time management skill (Nawrot and Doucet, 2014).
In this context, the Adaptive Semantic Web is a
framework that enables skill-based customization of
Web resources, including learning scenarios (Paquette
et al., 2015). In that work, learners were automati-
cally clustered into subgroups by their skills. These
clusters were more suitable to foster collaboration and
to adapt scenarios according to the cluster members’
needs. Unfortunately, the author claims that the mo-
del was not simple to implement, and students’ skills
identification should be at least partly automated con-
sidering that a human tutor approach is not feasible
for large groups.
Organizational learning is defined as the ability
of an organization to gain insight and understan-
ding from experience through experimentation, ob-
servation, analysis and a willingness to examine both
successes and failures (Sch
on and Argyris, 1996).
Companies that build structures and strategies in or-
der to increase and maximize the organizational le-
arning are distinguished as learning organizations.
In (Abel and Leblanc, 2009), organizational learning
is subdivided into three sub processes: Individual Le-
arning Process, Social Process and Knowledge Mana-
gement Process. Then, they are incorporated into E-
MEMORAe2.0 tool, designed for knowledge sharing
in an organizational learning context. A fully exploi-
tation of the traces in E-MEMORAe2.0 tool was used
to organize and improve collaboration (Wang et al.,
2015). Besides, the authors proposed a recommender
system based on the assessment of traces considering
the time decay of knowledge.
Organizations are using KMSs to facilitate kno-
wledge sharing. The way of interacting and sharing
knowledge depends on individuals’ skills and charac-
teristics. A experiment demonstrated that individuals’
perseverance in the tasks given and responsibilities ta-
ken positively influence their commitment with kno-
wledge sharing (Wang et al., 2014). LMSs also sup-
port the management of learning processes within or-
ganizations, enabling peer-to-peer knowledge capture
and sharing in a knowledge-based organization (Kline
et al., 2017). A LMS can manage all aspects of or-
ganizational learning alleviating the knowledge crea-
Assessment instruments are applied by organizati-
ons to measure their individuals’ skills. Bohlouli et al
defined a standard competence model with five main
skill categories and related sub-categories including
over 70 skill questionnaires in different managerial
WEBIST 2018 - 14th International Conference on Web Information Systems and Technologies
and employee levels (Bohlouli et al., 2013). Some of
these instruments and models are well known and wi-
dely used by organizations. Unfortunately, the moni-
toring and assessment process of each learner through
these instruments requires assessors to perform a sig-
nificant effort (Fidalgo-Blanco et al., 2015a), so ap-
plications based on learning analytics are needed to
alleviate the assessment process.
According to Siemens’ definition, learning ana-
lytics is the use of intelligent data, learner-produced
data, and analysis models to discover information and
social connections, and to predict and advise on lear-
ning (Siemens, 2010). Students’ performance in ge-
neric skills have been assessed through the collection
of students’ activity records with LMSs by means of
software based on learning analytics (Balderas et al.,
With the objective of providing answers to the requi-
rements of training and knowledge assessment in an
organizational environment, we propose the process
model shown in Figure 1. This process model in-
cludes several roles and both manual and computer-
assisted activities. All of these are aimed at the acqui-
sition and assessment of the participants’ skills in trai-
ning activities of a given organization. The process
model comprises the following sequence of activities:
1. Identification of Training Needs and Required
Skills: First, the manager in charge of organizatio-
nal learning within the organization identifies the
learning needs. Second, he/she designs a specific
learning plan. This plan lists the catalog of skills
expected for all learners. The manager maintains
the catalog of the skills and learning outcomes for
the organization by using a specific tool.
2. Design of Learning Activities: Subsequently, the
manager designs the learning activities needed for
the training plan by using the features of a KMS.
This way, he/she is able to monitor the learning
activities that learners are engaging.
3. Deployment of Assessment Instruments: By using
e-assessment systems, detailed feedback-enriched
assessment of learners can be supported.
4. Mapping Activities to Assessment Instruments and
Skills/Learning Outcomes: A conceptual model
containing the elements of interest involved in
this mapping is depicted in Figure 2. This mo-
del includes assessment instruments structured in
dimensions and sub-dimensions. Once the asses-
sment instruments have been deployed, the ma-
nager should indicate the skills and learning out-
comes that are developed by the learners through
learning activities. Then, it is necessary to make
a mapping among the involved activities, the sub-
dimensions of the assessment instruments, and the
skills and outcomes.
5. Engagement in Formative Activities: After setting
up the learning environment and the needed con-
figurations for the assessment, the training activi-
ties in which the learners are involved are carried
6. Performing Manual Assessment Activities: The
manager has to proceed with the assessment by
analyzing the learning results generated by lear-
ners. To perform this step, the manager uses the
assessment instruments previously created accor-
ding to the required skills.
7. Performing Computer-assisted Assessment Activi-
ties: The analysis of the learning results generated
by the learners may be partially assisted by using
specific tools developed for those purposes.
To support the organizational learning process propo-
sed, a set of tools were used, some of them specifi-
cally developed under open-source license:
Moodle Learning Management System to design
learning activities (activity 2).
EvalCOMIX to develop assessment instruments
(activity 3). Available in (EvalComix, 2011).
Gescompeval to map activities to assessment in-
struments and skills/learning outcomes (activity
4). Available in (Gescompeval, 2014).
EvalCourse to perform a computer-assisted as-
sessment based on learning analytics (activity 7).
Available in (EvalCourse, 2015).
The following subsections present these tools.
4.1 Learning Management System
To design learning activities, we have opted for using
Moodle as a LMS, a very popular and widespread
open source web-based system (Rice, 2006). We cre-
ated some specific tools to enrich Moodle with ma-
naging assessment instruments, managing skills and
analyzing learning activities by extracting desired in-
Assessment of Generic Skills through an Organizational Learning Process Model
Figure 1: Organizational process model for the assessment of acquired skills.
Figure 2: Conceptual model containing the main elements
of interest in the KMS.
4.2 EvalCOMIX
We used EvalCOMIX to carry out the e-assessment
activities in our architecture. It is a web service spe-
cifically designed to develop and manage different as-
sessment instruments such as scales or rubrics. Each
assessment instrument has its own structure based on
dimensions, sub-dimensions and attributes.
EvalCOMIX provides an API that can be integra-
ted with other e-learning systems to use designed as-
sessment instruments (S
aiz et al., 2010). Therefore,
a specific block called EvalCOMIX MD was imple-
mented to integrate EvalCOMIX with Moodle. As
other Moodle blocks, it is implemented in PHP and
JavaScript. EvalCOMIX MD provides three learning
assessment methods to be included in Moodle acti-
vities: teacher assessment, self assessment and peer
4.3 Gescompeval
We developed Gescompeval to manage skills and le-
arning outcomes in the proposed architecture. It
is a REST web service which provides a read-only
API to retrieve these skills and learning outcomes.
Gescompeval includes a web interface to handle ba-
sic CRUD (Create, Read, Update, and Delete) ope-
rations and to connect skills to learning outcomes
(and vice versa). Both API and web interface fol-
low a model-view-controller (MVC) architecture im-
plemented Symfony2, a PHP framework.
The integration of Gescompeval into Moodle was
carried out through the development of a Moodle 2.X
block extension called Gescompeval MD. This block
uses Gescompeval REST API to retrieve skills and
learning outcomes data in Moodle courses. Then,
this information can be connected to activities and as-
sessed applying EvalCOMIX assessment instruments
through EvalCOMIX MD. The overall integration ar-
chitecture between EvalCOMIX, Gescompeval and
Moodle is displayed in Figure 3.
The integration of EvalCOMIX and Gescompeval
WEBIST 2018 - 14th International Conference on Web Information Systems and Technologies
Figure 3: Skill management and e-assessment architecture.
with Moodle supports the assessment of specific skills
and learning outcomes for each learner and the com-
pilation of their grades. First, instructors have to se-
lect the required skills or learning outcomes by using
Gescompeval MD interface and then, they link them
to the corresponding sub-dimension of their EvalCO-
MIX tools. We display an example of this connection
in Figure 4. Second, skills/learning outcomes get the
grades from the sub-dimensions they are connected
with and combine those grades to get the overall grade
of their dimension. Finally, the grades for each skil-
l/learning outcome are displayed in a report to pro-
vide formative feedback. These reports are dynamic
graphics developed using Google Charts.
Figure 4: Selection of sub-dimension snapshot.
Gescompeval MD provides two types of feedback
reports. On one hand, a global report of all learners
who participate in the course is provided. This re-
port calculates the average grade of all learners’ gra-
des. On the other hand, individual reports with the
grades of each learner are also provided. Both re-
ports include an option to select if existing connecti-
ons between skills and learning outcomes must be ta-
ken into account to calculate the grades. Additional
information is displayed through a pop-up window
when users place the mouse pointer over a skill/le-
arning outcome graphic. This information includes:
code, name, value and those activities where the skil-
l/learning outcome were developed.
4.4 EvalCourse
Finally, we used EvalCourse, a standalone application
based on learning analytics that we developed to pro-
vide instructors with reports about students’ interacti-
ons with the LMS. EvalCourse was developed follo-
wing the model-driven architecture (MDA) methodo-
logy, to deal with concepts of an educational dom-
ain model. In particular, it executes queries coded in
SASQL, a domain specific language to easily design
online learning assessment on students’ generic skills
based on their interactions with LMSs (Balderas et al.,
2015), providing several reports with the information
EvalCourse supports two different configurations.
Firstly, it can be directly connected to the LMS da-
tabase. This is the desired operation mode, because
reports are based on live updated information. Unfor-
tunately, sometimes is not possible to obtain permis-
sion to establish a connection with the database of an
institutional LMSs. In these cases, it can work with a
backup of a LMS course, i.e. a snapshot of the records
of a course in a given moment.
This case study follows an authentic learning appro-
ach (Lombardi, 2007) in order to promote students to
explore, discuss and construct products in real-world
projects. In our case, this experience simulates a I.T.
company where employees in a project had to develop
a software system. The employees were six students
of Computer Science degree in their fifth (final) year.
They had to fulfill several milestones, each one with a
software deliverable for a certain deadline.
During their development tasks, they had to per-
form several generic skills. In this case study, the in-
structor posed tasks in which students should perform
the following skills: (a) ability to work autonomously,
and (b) ability to plan and manage time.
Then, students’ performance in those generic
skills were assessed following both the manual and
the computer-assisted methods within the organizati-
onal learning process proposed.
5.1 Manual Assessment
The instructor defined two assessment instruments
thorough EvalCOMIX, containing a dimension for
each generic skill. Each deliverable was assessed with
four attributes: correctness, efficiency, speed of exe-
cution and applied knowledge. They were assessed in
a scale of: none (one or no deliverable has the attri-
bute), some (at least two deliverables have it) and all
(every deliverable has it). Additionally, submission
time was assessed with one single attribute with four
values: delayed (submitted after deadline), average
Assessment of Generic Skills through an Organizational Learning Process Model
planning (submitted one or two hours before dead-
line), good planned (submitted one day before dead-
line) and excellent planning (more than two days be-
fore deadline).
Then, while students delivered their pieces of soft-
ware, the instructor assessed not only the technical
work well or badly done (specific skills), but also their
planning and their ability to work autonomously by
using Gescompeval.
5.2 Computer-assisted Assessment
Secondly, EvalCourse was applied in order to comple-
ment the former manual assessment. The first aspect
to analyze consists on checking if the students had de-
livered their assignments on time, delayed or even if
they had some pending assignment at the end of the
semester. The instructor can retrieve for that informa-
tion with the following SASQL code:
Evidence pieces_of_sw_delivered:
get students
show milestones
in assignment.
By using SASQL, the instructor can dynamically
redesign the query to or obtain information, contrast
an hypothesis and even check additional information
that can be used to assess a skill. For instance, the in-
structor detected that those students who delivered all
their pieces of software on time, had a greater number
of accesses to the LMS that the others. This informa-
tion was retrieved with the following SASQL code:
Evidence accesses_platform:
get students
show access
in campus.
Thus, the computer-assisted assessment gave the
instructor the opportunity to detect information about
students’ behaviour. This information was interesting
to assess one of the aimed skills and even some ad-
ditional ones. The following subsection discuss the
results obtained.
5.3 Discussion
Regarding the ability to plan and manage time, the
two assessments provide different approaches. On
the first hand, Gescompeval gives a better grade to
those students who submit their piece of software one
day before the deadline (good planned) or two or
more day before it (excellent planning). On the other
hand, EvalCourse gives the instructor a summary with
the number of pieces of software delivered, which of
them were delivered on time, and which of them were
not delivered. Figure 5 displays this comparison.
Figure 5: Comparison of both approaches for planning and
time management performance.
However, if we take into account Gescompeval re-
port for planning and time management and the acces-
ses to the campus obtained via EvalCourse, students’
numbers are more similar (Figure 6).
Figure 6: Comparison of students’ planning and time ma-
nagement with their accesses to the LMS.
It is important to highlight that the instructor could
assess other students’ generic skills not initially con-
sidered using EvalCourse reports. Figure 7 shows the
students’ grades in four generic skills performed by
the instructor with those reports: ability to plan and
manage time, capacity to learn and stay update with
learning, ability to be critical and self-critical and
ability to work autonomously.
Figure 7: Assessment of students’ skills via EvalCourse.
These assessments are interpretations that the in-
structor could assume with the obtained indicators,
but the validity of the application of these indicators
to a particular skill is outside the scope of this work.
We can conclude that the instructor could refine stu-
dents’ assessments with the objective indicators auto-
matically provided by EvalCourse. Actually, this is
WEBIST 2018 - 14th International Conference on Web Information Systems and Technologies
what concerns our proposal. To draw further conclu-
sions, this work requires deeper research, but it is a
valid first approach.
Although performance in generic skills is increa-
singly important for organizations to succeed in the
current competitive environment, its assessment in the
workplace remains as a challenging task.
In recent years, several alternatives to solve this is-
sue in educational contexts have been presented. Un-
fortunately, they rely on different activities that are
usually supported by isolated information systems. In
this paper, we have proposed a process model ultima-
tely aimed at automate the assessment of skills in a
KMS. We extended Moodle, a popular LMS, with a
set of specifically developed tools, such as Gescom-
peval, EvalCOMIX and EvalCourse.
The process model was tested by deploying a le-
arning experience to assess final-year undergraduate
students’ performance on several generic skills. The
experience was based on authentic assessment princi-
ples. On the one hand, the instructor mapped the acti-
vities to skills and performed the assessment by using
Gescompeval and EvalCOMIX. On the other hand,
the instructor applied EvalCourse to design queries
in a domain language to retrieve indicators about stu-
dents’ performance. These indicators were firstly ap-
plied to refine the previous assessment and secondly
to easily detect new indicators applicable to other
Results were promising, providing the manager of
the KMS with an automated process to assess diffe-
rent skills using objective indicators. Additionally,
students obtained detailed feedback, based on their
interactions in the KMS. Anyway, this part of the
process model needs further study to get a stronger
conclusion on its validity, as the use of Gescompeval
might present scalability issues if the organizational
learning have a high number of users. Nevertheless,
the computer-assisted assessment provided by Eval-
Course retrieves different indicators simply by wri-
ting a query, regardless of the number of participants.
Therefore, this is a positive evidence of its potential
when the number of users increase.
As a future work, we are enhancing the software
interface of the different tools developed so they can
be connected to other LMS different than Moodle.
This work was funded by the Spanish Government
under the Visaigle Project (grant TIN2017-85797-R).
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