Artículos
Messages from
university teachers to their students with low academic performance during
online teaching necessitated by COVID-19
Mensajes
emitidos por docentes universitarios a sus estudiantes con bajos desempeños
académicos durante la enseñanza en línea por COVID-19
Karla Lobos Peña klobosp@gmail.com
Universidad de Concepción, Chile
Fabiola Sáez-Delgado fsaez@ucsc.cl
Universidad Católica de la Santísima Concepción, Chile
Yaranay López-Angulo yara13190@gmail.com
Universidad Santo Tomás, Chile
Susana Arancibia Carvajal saranci@ucn.cl
Universidad Católica del Norte, Chile
Alejandra Maldonado Trapp alemaldonado@udec.cl
Universidad de Concepción, Chile
Messages from university teachers to their students with low
academic performance during online teaching necessitated by COVID-19
Interdisciplinaria, vol. 38, núm. 3, pp. 303-317, 2021
Centro Interamericano de Investigaciones Psicológicas y Ciencias
Afines
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Recepción:
02 Septiembre 2020
Aprobación:
23 Julio 2021
Abstract:
COVID-19 generated new forms of student-teacher interactions,
and it increased the use of virtual educational environments. Electronic
messaging is one of the most widely used forms of communication between
teachers and students. However, few studies on how teachers provide feedback
motivate and encourage students to engage in academic activities in online
learning environments. This study aims to characterize messages sent by
university teachers to their students with low academic performance during the
emergency remote teaching in the COVID-19 pandemic context. The electronic
messages were obtained through the snowball sampling technique. The sample
consisted of eighteen email threads facilitated by six universities. Ethical
requirements for this type of research were met, and discourse or text analysis
was used as a methodology with a qualitative approach and hermeneutic
orientation. This study shows two main results. First, the necessary data to
identify students with low academic performance can be mainly obtained from
their teachers and third parties, like university authorities. Second, there
are a number of elements to consider when creating messages to improve the
engagement of underperforming students. These fundamental elements are: tone of
voice, content of the message and moment in which the message is sent. Messages
that are explicitly written for each student or group of students and messages
that were written with anticipation, showed to be most effective in engaging
students.
Keywords: electronic messages, teachers, low academic performance,
university students, COVID-19.
Resumen: La COVID-19 generó nuevas
formas de interacción estudiante-profesor e incrementó el uso de ambientes
educativos virtuales, siendo la mensajería electrónica uno de las más
utilizados para la comunicación en las relaciones entre ellos. En este
contexto, el modo en que comunica el docente y los mensajes que emite, impactan
en variables académicas de estudiantes, sobre todo en estudiantes que tienen
bajos desempeños académicos. En la actualidad son escasos los estudios sobre la
manera en que el docente retroalimenta, motiva e impulsa al estudiante a
involucrarse en actividades académicas en los entornos de aprendizaje en línea;
por tanto, el objetivo de esta investigación fue caracterizar mensajes emitidos
por docentes universitarios a sus estudiantes con bajos desempeños académicos
durante la enseñanza en línea por COVID-19. Se utilizó el análisis del discurso
o de texto como método con enfoque cualitativo y orientación hermenéutica para
caracterizar los mensajes, considerando el sentido y significado de estos, lo
cual permitió rescatar la riqueza de los mensajes y analizarlos, en particular
aquellos que lograron alguna respuesta de compromiso por parte de los
estudiantes. Los mensajes de correo electrónico se obtuvieron a través de un
muestreo no probabilístico mediante la técnica de bola de nieve. La muestra
estuvo constituida por 18 cadenas de mensajes de correo, facilitados por seis
universidades, que fueron emitidos durante la enseñanza en línea por COVID-19.
Se cumplieron con los requerimientos éticos para este tipo de investigación. El
análisis de los datos se realizó a través de tres grandes pasos: (1) revisión
de la información; (2) identificación de las unidades de análisis, y (3)
categorización. Dentro de los principales resultados se encuentran: (1) docentes
y terceras personas (autoridades) son las fuentes de información que permiten
identificar a estudiantes con bajos desempeños académicos; (2) los mensajes que
utilizan los profesores para comunicarse con sus estudiantes poseen
especificaciones en el tono comunicacional, contenido y momento de la
comunicación que favorecen el compromiso de aquellos estudiantes que presentan
bajos desempeños académicos, siendo los mensajes personalizados, anticipados y
con alternativas propositivas los más efectivos, y (3) los mensajes emitidos
por docentes que favorecen algún tipo de compromiso de los estudiantes son los
que: utilizan un tono comunicacional personal, presentan contenido de
preocupación y/o de aliento, comunican tempranamente evidencias de
incumplimientos que permiten la detección, y ofrecen alternativas concretas que
puede utilizar el/la estudiante para revertir la situación de incumplimiento o
bajo desempeño. Además, se pudo observar que los profesores, en la comunicación
con sus estudiantes, utilizan con frecuencia contenidos, evidencias y mensajes
instructivos, y la razón fundamental que emplean en el mensaje es la ausencia
de registro de alguna calificación. La mayoría de los docentes que participaron
de este estudio envían los mensajes cuando aún les resulta posible ofrecer
oportunidades al estudiante para revertir su situación académica, con
frecuencia utilizan un tono de comunicación personal y el de tercera persona
(impersonal), por sobre el tono institucional. Se entregan orientaciones para
el diseño de mensajes electrónicos más efectivos que permitan revertir
situaciones de desempeño insatisfactorio. Se concluye que para comunicarse con
los estudiantes es importante diseñar mensajes con características específicas
que los hagan más efectivos.
Palabras clave: mensajes electrónicos, docentes, bajo desempeño académico,
estudiantes universitarios, COVID-19.
Introduction
The evidence of the importance of teacher-student interactions
in improving students' learning skills and educational outcomes has been strong
(Blegur, 2019; Chohan, 2018; Kumi-Yeboah, Dogbey, & Guangji, 2018; Laudadío & Mazzitelli, 2018; Pianta, 2016; Tsai, 2017; Wang & Neihart, 2015). The most
relevant and efficient feedback that a student can receive corresponds to the
one that is sent by their teacher (Harper,
2018; Lobos, Diaz, & Bustos, 2019;
Prewett, Bergin, & Huang, 2019).
In this context, teachers must seek pedagogical training in effective
communication skills in education. When teaches communicate in an effective
way, they can improve students’ self-regulation skills (Cardoso-Bello, 2011) and become a role
model for their teaching peers (Turanbayevna
& Xusenovna, 2020).
Education during the COVID-19 pandemic has required a rapid
response from educational authorities to guarantee the right to learn. Teachers
worldwide have been forced to continue their classes remotely, this situation
is commonly called emergency remote teaching ERT (Giannini, 2020; Xarles & Samper, 2020).
Remote education is perceived as a threat to the teacher-student
relationship because both virtual learning environments and learning management
systems (LMS) are not always user-friendly for monitoring student’s behaviors
as compared to traditional face-to-face education (Lobos, Bustos-Navarrete, Cobo-Rendón,
Fernández, Bruna, & Maldonado, 2021; Van Der Spoel, Noroozi, Schuurink, & Van
Ginkel, 2020). ERT does not replicate face-to-face education, and it is
still obscure for teachers and educational managers (Quezada, Talbot, & Quezada-Parker, 2020; Slevin, 2008). However, this teaching
modality has benefits that include technological tools, resources, and
activities supporting and promoting interaction (Kim, Hong, & Song, 2019).
In the context of ERT, the greater challenge for teachers is to
develop strategies that allow them to relate to their students using the
advantages of remote education and learning management systems (LMS; Ashrafi, Zareravasan, Rabiee Savoji, &
Amani, 2020). These include having quick access to performance information
(Godwin-Jones, 2012), such as whether
the student is connected, has performed online activities, is viewing
resources, handed in assignments, and what grades they have obtained. Another
advantage is the varied communication channels it offers, such as
videoconferencing, chat, and forums (Crawford,
Butler-Henderson, Rudolph, Malkawi, Glowatz, Burton & Lam, 2020; Ramirez-Anormaliza, Sabaté, Llinàs-Audet,
& Lordan, 2017). All these interactions between the students and the
LMS can be accessed by researchers through files called “tracking-logs”. The
analysis of this information is usually referred as learning analytics (Aldowah, 2019).
The use of student performance data in virtual educational
environments, combined with the opportunities offered by messaging systems has
facilitated new communication opportunities in teacher-student relationships (Domonkosi & Ludányi, 2019). The most
commonly used intervention method to address students' academic performance
involves offering personalized recommendations to students by viewing data on
their learning processes through these channels (Wong & Li, 2019). Messaging systems
allow sending text messages from one user to one or more users using a
communication network. Users can send short or multimedia messages (SMS or MMS)
without an Internet connection using their mobile network or instant messages
through an Internet connection. Messages can be used synchronously and
asynchronously (Iglesias, Lozano, &
Martínez, 2013).
In education, messages can be synchronously and asynchronously (Iglesias, Lozano, & Martínez, 2013).
Examples of synchronous uses are chats, while examples of asynchronously
messaging are emails and discussion forums. The latter being the most used for
formal communications in universities (Chavez,
Del Toro, & Lopez, 2017; Ladino,
Bejarano, Santana, Martinez, & Cabrera, 2018). In the study, Christy-Dale L. Sims (2015), the author
proposes that email communication allows for quick responses that help meet
students' needs, particularly for high-risk students, improving their chances
of success. The author identifies five standards to distinguish between
appropriate and inappropriate emails.
1) Personal: contains an individualized salutation and signature
2) Accurate: has a precise subject line and addresses the topic
at hand.
3) Prepared: checked responses before sending and included
pertinent information.
4) Polite: uses a basic formal tone and courtesy such as
“please” and “thank you.”
5) Proof reading: spelling, grammar, accuracy, and tone.
In Sarsar (2017) study,
the author verifies the effectiveness of motivational feedback messages from
teachers to students in the virtual learning environment. The results show that
teachers' feedback regarding students' behaviors and results is the most
relevant element for engaging and motivating students to study. The author
points out that feedback is fast, fluid, and a constant process of genuine
interaction between teachers and students in face-to-face classrooms. Although
communication channels for implementing feedback are usually restricted in
virtual environments, it is crucial to provide feedback constantly to maximize
its effectiveness.
Some studies investigate how feedback messages improve and
maintain students' motivation levels (Cheng,
Liang, & Tsai, 2015; Maier, Wolf,
& Randler, 2016). For example, Sarsar
(2017) used a motivational feedback message approach, which provided
feedback utilizing achievement recognition strategies and reinforcement or
praise. This type of message can motivate extrinsically (as reinforcement) and
intrinsically (as an encouragement to learn). Three types of messages have been
proved to impact students positively. These three are messages of
encouragement, messages of praise or recognition, and messages with
instructions (Lobos et al., 2019; Lobos, 2020). The praise or encouragement
components must always be accompanied by an instructional message; otherwise,
these types of messages are insufficient to promote student motivation. When
using encouragement or praise and pointing out exactly what the student did
well that deserves recognition or what needs improvement (instructional
message), the messages are linked to concrete facts, making them credible and
personalized for the learner (Lobos, 2020).
The semantic value of words and their meaning affect students'
emotions (Anusha & Sandhya, 2015; Goddard, 2011). Unfortunately, messages
sent in virtual learning environments are primarily composed of text. This
means that the only way to add emotion in online feedback messages is to use
the meaning of words as a strategy to capture students' attention (Sarsar, 2017). In text-based feedback,
emotions are primarily represented by words. Therefore, word selection is
critical in creating an emotional response. For example, if a teacher writes
“Great job!” it can make students feel glad, whereas “Good job!” might elicit a
positive but less intense response (Sasar,
2017).
Previous evidence points out that individualized messages
generate higher motivation levels than impersonal messages, especially
regarding trust between student - teacher. In addition, students who receive
personalized feedback are more satisfied, willing to learn, and achieve high
academic performance than those who only receive collective or general feedback
(Gallien & Oomen-Early, 2008).
In this context, how teachers communicate and the messages they
use, significantly impact students' academic motivation. Teachers are not aware
of this impact on the affective, cognitive, and behavioral aspects, especially
in students who present higher difficulty for learning (Lobos, Díaz, Bustos, & Sáez, 2018).
There are many studies on feedback, emotion, and motivation. However, research
that addresses the relation between virtual learning environments and the
effectiveness of electronic messaging is still scarce (Sarsar, 2017).
Based on the literature, the following assumption is made: the
uniqueness (closeness, affective tone, pro-positivity, among others) of
interaction through emails between teachers and students affects students'
engagement with low academic performance. The present study proposes to
characterize teachers' messages to their students with low academic performance
during the emergency remote teaching modality due to COVID-19 in the context of
higher education. For this purpose, the objectives of the study are defined as:
1) to distinguish the sources that allow the identification of
low academic performance,
2) to describe the qualities of teachers' messages for students
with low academic performance, and
3) to recognize characteristics of messages given by teachers
that favor the engagement of students with low academic performance.
Method
A qualitative approach with a hermeneutical orientation was used
(Denzin & Lincoln, 2011/2012). The
messages were analyzed considering what was inside and outside of them; that
is, their sense and meaning, which allowed the interpretation of their
richness, enabling their characterization, particularly of those that elicited
some response of engagement by the students.
Sample
The sample consisted of 18 - email thread in the pedagogical
interaction of university teachers and students online during the COVID-19
pandemic. The senders and receivers of messages were from six Chilean
universities and the first academic semester of 2020, placed in the context of
virtualization forced by COVID-19. The final sample size was specified when the
theoretical saturation criterion was achieved, at which point the collection of
electronic messages was stopped as no new information relevant to this study’s
objectives emerged. Electronic messages were obtained from communications
between teachers and students of physical and mathematical sciences, biological
sciences, and social sciences.
Data collection procedure and ethical considerations
Electronic messages were obtained using the snowball sampling
technique, in which initial teachers voluntarily recruited additional users for
the study.
Faculty from the six universities participating in the project
COVID-1012 were asked to voluntarily provide email threads that they used
during the 2020 first academic semester. The messages approached the
performance shown by first-year students who were in disadvantage respect to
their classmates. The initial teachers requested messages from their teaching colleagues.
These professors teach first-year courses in their same disciplines. Eighteen
email threads was used, facilitated by nine teachers.
Regulations and ethical principles of the investigation were
taken into account; an informed consent signature was requested to make used of
the messages and the personal data of both the sender and the recipient of the
electronic messages was protected.
Procedure for the analysis of the results
The data analysis was carried out in three steps: (1) review of
the information, (2) identification of the units of analysis, and (3)
categorization and coding. For the content analysis, units of analysis were
identified, categories were generated, a coding scheme was developed,
categories were compared, dimensions were identified, and finally it was
interpreted. Content analysis was performed without software support.
The coding and reordering of categories is an iterative process
based on a permanent comparison of data, readings, and re-readings. The coding
of the messages continued until the theoretical saturation of the categories
generated was reached, that is, until the new data no longer added new
information (Krause, 1995). The
frequency of the messages and their general characteristics were identified in
the coding of the content of the messages.
Through descriptive analysis, a range of contents and meanings
implied in the forms of identification and support messages used by teachers
with their students was obtained. Likewise, this analysis made it possible to
identify the main components and organize these contents hierarchically (Denzin & Lincoln, 2012). The analysis
process delved deeper into the semantic level of communication.
Analysis of the results
The analysis of the messages sent by teachers to their students
made it possible to identify four central categories that allow the
characterization of messages from teachers to students with low academic
performance (Table 1). The results are presented below based
on the objectives established in this research.
Table 1
Categories |
Dimensions |
N |
Examples of Messages |
|
Forms of identification |
Absence of note in official registry |
10 |
55 |
“I noticed that I do not have your grade for
the paper” (email thread 3). |
Failure to send assignments |
6 |
33 |
“Your paper has not been uploaded to the
Teams folder” (email thread 10). |
|
Difficulty report from classmates |
1 |
5 |
“Your classmates let me know that you have
missed several classes” (email thread 5). |
|
Difficulty report from managers |
1 |
5 |
“I have been informed by the Career Director
that you are...” (email thread 7). |
|
Communicational tone |
Informal staff |
8 |
44 |
“Hello, I am writing to you because of...”
(email thread 14). |
Formal staff |
10 |
55 |
“Along with greetings, I am writing to
inform you that...” (email thread 17). |
|
Institutional |
2 |
11 |
“At the request of the Head of Career I am
contacting you to...” (email thread 1) |
|
Content |
Encouragement |
10 |
55 |
“I know you can re-organize your time and
catch up”... (email thread 12). “Cheer up, I will help you to review the
video...” (email thread 6). |
Praise |
2 |
11 |
“You always participate in class...that is
appreciated especially in this virtual format” (email thread, 4). |
|
Evidence |
16 |
88 |
“There are missing grades due to
non-delivery of assignments”(email thread 9). “Test n°2 and n°5 are
unanswered, remember that you have until...” (email thread 10). |
|
Instruction |
15 |
83 |
“Check the video for instructions to attempt
the test” (email thread, 8). “Connect through this link... at 12.00 hrs. to
attempt the test” (email thread 15). |
|
Concern |
4 |
22 |
“If you have any problems, let me know,”
(email thread 15). “I am concerned about your absence from class,” (email
thread 9). “I haven't received your work yet” (email thread 16). |
|
Moment of communication |
Anticipated |
6 |
33 |
“I haven't received your work yet... the
deadline is next Monday” (email thread 1). |
Contemporary |
11 |
64 |
“I will activate the test in the virtual
classroom for you to take on ....” (email thread 15). |
|
Extemporaneous |
1 |
5 |
“You have a minimum grade on the record ....
as you have not turned in the guide.... If you have any justification, send
it to the Career Director” (email thread 11). |
Note: The percentage refers to the proportion of email thread that
present the indicated characteristic out of a total of 18, which would
correspond to 100 %.
Forms of identification of students with low academic
performance
The results reflect two sources of information for identifying
students with disadvantaged academic performance. The first is information
contained in the messages about the students' performance, which reflects some
type of non-compliance or low performance that places the student in a
disadvantaged position in the subject. For example, the absence of a grade
record and the student’s failure to send a required academic activity within a
certain period: “According to the grade record, you have a summative test
pending in...” (Email thread 15); “I have reviewed the deliveries and I have
not received your work of...” (Email thread 14). This type of identification
reflects the monitoring of student learning with the use of traditional
indicators that, although recorded in the learning management platforms (LMS),
do not include the use of student interaction information in the virtual
classroom.
The second source of information is reports from third parties
(peers, other teachers or career managers), who inform the teacher that a
certain student is in a risky situation that may affect his/her academic
performance: “Your classmates informed me that...” (Email thread 5); both
sources motivate the development of personalized messages to disadvantaged
students.
Qualities of teaching messages to students with low academic
performance
Analysis of the messages reveals three categories of message
qualities: (1) communicative tone, (2) content, and (3) timing of
communication.
Communicative tone
Three types of communicational tones were found: informal
personal, formal personal, and institutional impersonal. The informal personal
refers to the tone where the teacher communicates in the first person and
delivers the contents of the message revealing an interest in the student's
improvement: “Hello XXX, I am concerned about not having received your critical
analysis...” (Email thread 15). The second type is where the teacher
communicates formally expressing their concern about the student's situation:
“Dear Student, I am communicating with you, since I have noticed that your note
of...” (Email thread, 8). The third type is characterized by a communication
that depersonalizes the intention of the teacher in sending the message and
places it in the interest of others, outside the subject: “On behalf of the
head of the course, I am communicating with you” (email thread 10).
Content of the message
Three types of content were observed: affective (praise,
encouragement, and concern), evidence of academic performance, and instruction
for change.
The affective component of a message takes several forms:
praise, where the teacher alludes to some aspect of success or positive quality
in the student's performance that catches their attention and motivates the performance
approach communication: “I’m sure you always do an effort and you keep trying”
(email thread 12), of encouragement, where the teacher sends a message of
encouragement that seeks to motivate efforts towards improvement: “Everything
has a solution. Cheer up and count on me to help you” (email thread 3); and
concern, where the teacher lets the student know that they are interested in
their situation and opens new possibilities for interaction: “You can ask me
questions through this channel,” (email thread 2).
The performance evidence component refers to message contents
that indicate objective data and information, previously collected, on which
the teacher relies to point out the need for improvement in the student’s
academic performance. This evidence would be related to low grades and/or
non-attendance, failure to meet deadlines for academic commitments, and special
situations reported by other educational actors: “I am writing to you because I
have already uploaded the final grades of ... to the system and I still do not
have yours” (email thread 12).
The instruction for change component in the message is when the
teacher provides concrete alternatives to revert the situation of
non-compliance or low performance to the student. These include indications
that guide the student about what to do in their particular situation: “The
test will be published tomorrow at 12:00 noon, you will have 30 minutes to
answer it” (email thread 15).
Timing of communication
Three temporal dimensions were identified: anticipatory,
contemporary, and extemporaneous, which distinguished communication according
to its purpose.
Anticipatory messages address an assignment that has not yet
become a non-compliance or failure; therefore, the student does not require
special treatment to reverse the situation. They function as reminders that
place the control of improvement with the students: “I consulted with the
assistant and he tells me that he has not received anything from you, but that
the deadline has not yet expired” (email thread 2).
Contemporary messages concern non-compliance or poor performance
that have already occurred, but where the alternatives to revert the student's
situation are under the teacher's control: “We are already finalizing the
activities in the subject, you can take the pending test the week of” (email
thread 5).
The extemporaneous messages address non-compliance and poor
performance, which cannot be reverted or cannot be reversed by the teacher, but
require the action of third parties (Directors) or other instances of the
educational institution: “You should must discuss your situation with the
Career Director, since this current condition is NCR [does not comply
requirement] and he would be failing on the subject” (mail thread 7).
Characteristics of messages issued by teachers that elicit
student engagement
Messages that elicit student engagement response (e.g.,
expressing the intention to follow the teacher's directions or requesting more
information to reverse the disadvantaged situation) have the following
characteristics:
- The communicative tone is personal, and the greater the number
of attempts, the more personal and informal is the communicative tone.
- They communicate early evidence of noncompliance, which allows
detection.
- They offer concrete alternatives that the student can use to
reverse the situation of noncompliance or underperformance.
- They express concern and/or encouragement.
Regarding the prevalence of the characteristics found in the analysis
of the email thread, the absence of recording any note is the most frequent
reason for identifying a student with low commitment. In such cases, the
evidence and the instructive message is the most used to communicate with
students. Most teachers send messages when it is still possible to offer
opportunities to the students to reverse their situation, and the prevailing
tones of communication are personal and third person (impersonal), over the
institutional tone.
Discussion
The overall objective of this study was to characterize messages
sent by university teachers to students with low academic performance during
the emergency remote teaching modality imposed by the COVID-19 pandemic. The
main findings are discussed below, limitations are described, and future
research directions are projected.
One of the first objectives of this study was to identify the
data sources that allowed identify students with low academic performance. The
students' interactions with the learning management system of their university
can be analyzed from the LMS tracking logs. Examples of these interactions are
discussion forum participation or chat use. The teachers can use these
analytics to make data-driven pedagogical decisions to increase students'
performance and engagement with the course resources (Dias et al., 2020).
Our results show that teachers' motivations to approach students
by messages are related to academic noncompliance or difficulty in recording a
grade—this teaching traditional approach evidence the absence of other sources
of information provided by the ERT context (Saíz-Manzanarez
et al., 2019). Different authors justify this situation arguing that
teachers do not necessarily know about the existence of learning analytics
reports provided by LMS or other institutional platforms (Ashrafi et al., 2020; De la Iglesia, 2020).
The second identified data source for obtaining students'
behaviors depends on third parties such as academic authorities. In some cases,
they are the only ones with access to the information. In these situations,
learning managers urge teachers to pay special attention to students with a
higher probability of academic failure.
Another objective of this study was to describe teachers'
messages to students with low academic performance. The characteristics found
to allude to the communicative tone of the text, different types of content,
and the academic situation in which communication occurs. Good communication
abilities teachers allow obtaining better results with their students. This
ability is considered a fundamental skill, essentials to be an integral teacher
(Ibáñez, De Benito, & Carrió, 2014).
Regarding communicative tone, three types were identified:
informal personal, formal personal, and institutional impersonal. The first two
allude to the teacher's interest in the improvement of the student, as opposed
to the third, which is characterized by a communication that depersonalizes the
intention of sending the message and places it in the interest of others. The
difference between the first two is that the informal personal tone is
characterized by a close and colloquial language that communicates a certain
familiarity with the student, as opposed to the formal personal tone where
serious and prudent language is used and colloquialisms and relaxed phrases are
avoided. Dickinson's study (2017) on
the use of electronic messaging in an online class highlights the importance of
this finding by indicating that a close personal tone in emails is related to
better performance in students.
The five types of content can be subdivided into
affective-motivational (praise, encouragement, and concern for their academic
situation) and informative (evidence of poor academic performance and
indications to reverse the situation). The former help the students recognize
aspects of themselves that could be a source of motivation for improvement
(recognition of skills and confidence in his ability to improve), which
transmits high expectations and stimulates their perception of self-efficacy in
the face of learning (Hampton et al., 2020;
Wang, Rubie-Davies, & Meissel, 2018).
Messages of concern, on the other hand, stimulate closer relationships with the
student by offering help and conversational spaces. The second subtype gives
credibility to the message by revealing objective information that the teacher
monitors their academic performance (Lobos,
2020), and the teacher’s genuine involvement to improve the student's
learning experience by showing concrete alternatives to improve the
insufficient performance.
As for the temporality of the messages, three types were
identified: anticipatory, contemporary, and extemporaneous. The differences
between these are found in their purposes. The first functions as a reminder
for the student, helping them to self-regulate their learning, implicitly
inviting the student to better organize their time and prioritize activities (Sáez, et al., 2018), and placing the
control of improvement in the student’s hands, avoiding procrastination and
anxiety (Manchado & Hervías, 2021).
Contemporary temporality messages are those that report non-compliance in
academic performance and require a response from the student to reverse the
situation. In these, the teacher who decides to give students new
opportunities. Extemporaneous messages function as notifications, reporting
non-compliance and failures in academic performance that can no longer be
reversed by the teacher and require external intervention by the educational
institution for their solution.
Finally, elements of the electronic messages that elicited a
commitment response were identified. The characteristics identified in these
messages take the form of evaluative interactions (Lobos, 2020). This type of teacher-student
interaction encourages a sense of greater competence and autonomy by
distinguishing a teacher who trusts in students’ abilities and possibilities of
improvement, while promoting a positive emotional bond, greater motivation
toward the achievement of academic goals, and greater perseverance on tasks of
greater cognitive complexity.
Research in which teachers’ communication skills are studied
shows three key goals involved in the communication process (Camus, Iglesias, & Lozano, 2019).
These objectives are to inform, affective motivate, and self-regulate students.
By delivering to teachers concrete instructions on writing compelling messages,
they can improve their teaching and learning process (Cardoso-Belo, 2011; Ibáñez, De Benito, & Carrió, 2014).
It is important to note that in this study, the number of cases
was limited, which limits the scope of its results. This is particularly
noticeable in the analysis of the differences between messages that increase
the possibility of students' academic engagement response versus those that do
not, given that the number of strings that achieve student response is greater
than those that do not. This could be determined by an involuntary selection,
made by the participating teachers, of those email thread where there is an
exchange of messages with the students.
Future studies should broaden and diversify the sample (for
example, students who are not in their first year of study, from different
educational levels and from careers in different areas of science) to enrich
the knowledge on this subject and improve the effectiveness of teachers’
messages. Experimental studies would help establish the impact of these
messages on different desirable behaviors in students and on their educational
outcomes.
Increasing the type of messaging is also of interest, given that
due to the conditions of emergency remote education, teachers have started to
use other virtual means of communication with their students, such as chats and
forums in virtual classrooms and WhatsApp, among others, which have other
characteristics. A good starting point would be identifying whether these are
perceived as useful by students to improve their academic performance.
Comparative studies between the use of different means of virtual interaction
and their relationship with better educational outcomes would help to develop
guidelines for educational policies in higher education, associated with the
selection of LMS and the functionalities they provide in this area.
Conclusions
This study provides valuable information for higher education
teachers willing to invest time in helping their students with unsatisfactory
academic performance. In addition, it provides evidence-based guidelines for
creating electronic messages to effectively communicate with their students to
create engagement with the course and improve unsatisfactory performance. The
results show the extreme importance of the personal tone in writing messages to
students with low academic performance. In the messages, teachers should
explain the situations that justify their concerns and must include precise
instructions to reverse students' academic situations. In addition, messages
need to be sent promptly to obtain the desired effect. Finally, the results
also show the efficacy of using affective expressions of motivation. These must
show genuine concern on the teacher's behalf for the student's improvement and
wellbeing.
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