Teaching planning in remote education

The organization and incorporation of elements that fit remote education into planning is essential to ensure that no student is left behind (^{AZNAR SALA, 2020}). This has meant curricular adjustments according to the criteria of virtual times (synchronous and asynchronous), resources, methodologies, strategies, and evaluations that allow the achievement of curricular objectives prioritized to mitigate the effects of the learning gap resulting from the health emergency.

The adaptations to the teaching planning “have demanded greater dedication in the preparation of the subjects than the one destined in the face-to-face format” (PEREZ-LOPEZ; VAZQUEZ ATOCHERO; CAMBERO RIVERO, 2021, p. 343). Thus, curriculum design in remote education is constituted by the preparation and adaptation of teaching and learning according to curricular decision-making; the specification of this design as a class session or development that requires synchronous or asynchronous didactic strategies.

Methodologies in remote education

The virtual context has required a pedagogical change oriented toward the implementation of methodologies that facilitate self-learning, interdisciplinary work, collaborative learning, based on projects, problems, or other active methodologies. This new reality requires greater dynamism, flexibility, and autonomy for the development of student-centered learning (^{BUSTAMANTE, 2020}). In fact, methodologies or strategies that are specific to classroom teaching cannot be replicated (^{STEWART, 2021}).

The challenge is to build a teaching and learning process that collaborates with student autonomy and active participation (^{MORGAN, 2020}). Consequently, it is hoped that these methodologies will allow the development of “activities that motivate analysis, critical thinking, reflection, and the collective construction of knowledge” (GALINDO et al., 2020, p. 10), so that they respond to contextual, cognitive, and emotional needs differentiated according to the virtual spaces of link between teachers, students, and among students. Likewise, this implies how synchronous and asynchronous modes allow interaction, metacognition, and academic motivation. These are fundamental and critical aspects (ZACCOLETTI et al., 2020) that have had a significant impact on students due to the absence of presence and the increased sense of social isolation.

Didactic resources in remote education

According to ^{Arriagada Toledo (2020)}, teachers have had to reinvent themselves and incorporate new educational tools and materials to confront teaching and learning in the different virtual environments imposed by remote education. This leads to the need to use a range of digital teaching resources that are essential to ensure the teaching and learning process (^{PICÓN, 2020}).

Due to the absence of classroom classes, didactic resources or educational materials must be adapted to the new digital methods that are used in the formative processes because they have to consider the technological gaps among the students, which represents a great challenge for the teachers (MACINTYRE; GREGERSEN; MERCER, 2020). Indeed, in the face of this unknown educational reality, the demand for the preparation of teaching resources requires more time for their production and preparation (PÉREZ-LOPEZ; VAZQUEZ ATOCHERO; CAMBERO RIVERO, 2021).

Evaluation for learning in remote education

An e-assessment in virtual learning environments (^{BARBERA, 2016}) becomes a possibility for the consolidation of an authentic assessment or for learning in remote education. This demands a formative assessment with a strong component of effective feedback (RUÍZ-PRIMO; BROOKHART, 2018), which allows the construction of learning in synchronous and asynchronous spaces. The transformation of evaluative practice for online learning requires the development of relevant assessment to enhance formative evaluative coherence (COVID-19 SOCIAL EDUCATION TABLE PROPOSALS, 2021) and, thus, avoid replicating a face-to-face evaluative practice (^{HODGES; FOWLER, 2020}).

The challenge lies in the development of a diverse, continuous, feedback-oriented formative evaluation model with active student participation (PHALARADRA; ABEYWARDENA, 2016; ^{RAHIM, 2020}; YAO et al., 2020). Online evaluative practice implies a flexible attitude on the part of teachers for the implementation of evaluative strategies and instruments relevant to the remote modality.

Finally, remote education requires a redesign of the evaluation system aimed at developing authentic, contextualized, decentralized evaluation experiences that integrate learning in synchronous and asynchronous spaces, accompanied by systematic feedback practices as a way to strengthen teaching and learning processes (GARCIA-PENALVO et al., 2020; MUNOZ RIVERS; HERRERA ARAYA, 2020).

Social interaction in remote education

Social interaction as socio-affective relationships in the classroom (ESCAMILLA et al., 2020) has had a negative effect on the achievement of learning in the remote modality. In this way, the social construction of teaching-learning is fundamental for the exchange of ideas, as it enables multiple communications based on argument and reflection. These socio-educational processes require socio-affective support linked to motivation and academic achievement (ZACCOLETTI et al., 2020).

It is important to mention that this link is not only related to academics, since the closure of schools has generated a heightened sense of loss and isolation among students (^{MILLER, 2021}). Therefore, teachers have had to emotionally assist their students (^{BUSTAMANTE, 2020}) in order to accompany and reinforce socio-affective support and academic motivation as facilitators of learning in remote education (^{MILLER, 2021}). Thus, the construction of spaces in remote education based on trust is of vital importance (GALINDO et al., 2020) and as an opportunity to reassess and reinvent relational ties through a sociopolitical practice of active-authentic care (^{MILLER, 2021}).

Pedagogical support in remote education

Institutional pedagogical support is essential to consolidate the teaching and learning processes in remote education, both at the level of technical support and in the professional development of teachers (GARCIA ARETIO, 2021). This support not only consists of guidelines and training for the effective use of digital resources, but also involves continuous digital training processes that enable the creation of virtual learning environments (PORTILLO PENUELAS et al., 2020). Pedagogical accompaniment refers to the assistance they received for planning and coordinating teaching actions for the effective construction of virtual learning environments, together with the strengthening of their methodological and technological skills for remote education (GARCIA ARETIO, 2021).

Thus, teachers in this context of health emergency with migration to remote training are exposed to different challenges related to methodological and didactic changes, evaluation strategies, the use of technologies, and the link they establish with their students. Both for pedagogical challenges and for the development of practice in remote education, collaborative work, together with agile pedagogical-institutional support, is fundamental to face these new forms of teaching (AZNAR, 2020).

Construction of the questionnaire

The questionnaire was constructed through an iterative process (^{LÓPEZ-ROLDÁN; FACHELLI, 2015}) by three evaluators. This process was structured by technical processing sequences presented in detail in Table 1.

Based on the technical sequences of the questionnaire, the instrument is composed of the dimensions that were defined according to the revised literature (GALINDO et al., 2020; ^{HODGES; FOWLER, 2020}; PEREZ-LOPEZ; VAZQUEZ ATOCHERO; CAMBERO RIVERO, 2021; SIMON; MUNOZ-MARTINEZ; PORTER, 2021; YAO et al., 2020). These dimensions considered the research focuses linked to the design and validation of questionnaires in remote education (FANDOS-IGADO et al., 2021; ROMO-SABUGAL; JUAREZ-HERNANDEZ; TOBON, 2021; VILLARROEL et al., 2021), with the aim of establishing greater precision and delimitation with respect to the operationalization of the teaching-learning construction in remote education. The dimension are presented in Table 2.

According to these definitions, the six dimensions that make up the questionnaire were operationalized in different indicators (items) in the form of positive phrases. For each of the items, a Likert scale with four levels of agreement was used. These indicate are described in Table 3.

Validation

After completing the analysis of the overall and specific relevance and coherence of the questionnaire, which made it possible to develop the internal adjustment through the application of an iterative intra- and inter-item review for each dimension of the instrument, we proceeded to the process of validation by expert judgment to ensure the content validity of the questionnaire. Content validity is defined as the degree of positive relationship to measure the effectiveness of the theoretical construct according to the items that compose it (^{RUIZ BUENO, 2014}). This process is known as an item analysis (^{LOPEZ-ROLDAN; FACHELLI, 2015}), which makes it possible to guarantee descriptions or inferences from the results obtained.

The questionnaire was validated by five expert trials by adapting the Escobar-Pérez and Cuervo-Martinez validation criteria (2008). The validators have graduate degrees in education with a specialization in curriculum and evaluation, work in higher education and school contexts, and have more than ten years of teaching and research experience. A coefficient of expert competence was applied to each of the experts (^{CABERO ALMENARA; BARROSO OSUNA, 2013}), according to the assessment variables on the level of knowledge of the subject (content) and its level of argumentation. The results showed a high value of expert competence for each one (0.8-0.9).

Thus, the criteria used for the validation process were:

Based on these criteria for content validation or item analysis, the questionnaire experienced a minor adjustment in the wording of some indicators related to verbal and temporal formulations. These adjustments were: (a) verb tenses from present to past, (b) lexical revision to specify the element(s) that constitute the indicators, and (c) precision of elements with the use of parentheses to specify some indicators in relation to categories such as “learning,” “educational materials,” “technological tools,” and “virtual platforms.” In addition, it obtained the maximum score for each of the dimensions based on the evaluation made by the five expert judgments according to the high level of compliance with relevance and coherence, which allows guaranteeing its intra- and inter-item validity.

Reliability

The questionnaire was applied to a sample of 202 teachers with a dual purpose: to test its overall reliability and by dimensions (^{RUIZ BUENO, 2014}) and to collect information on the construct of teaching and learning in remote education to evidence its validity. Thus, the purpose of evaluating the reliability of the questionnaire was to:

In this way, the questionnaire was analyzed internally by calculating Cronbach’s Alpha coefficients globally and for each of its component dimensions. This methodological exercise ensures the consistency of the questionnaire for the collection of empirical data (^{TABER, 2018}).

The non-probabilistic sample distribution used for the application of the questionnaire is presented in Table 4.

From the application of the questionnaire, a reliability analysis was carried out with the application of SPSS software, version 22, to determine the properties of the instrument by calculating the reliability measures of scales and the intra-item correlation of the instrument in order to establish the internal consistency according to the average of the correlations between the items. From the analysis carried out, it can be indicated that the result of the intra- and inter-item consistency analysis is reliable, given that for all the indicators that constitute the dimensions of the questionnaire it is positive (^{MUÑIZ; FONSECA-PEDRERO, 2019}). The results of the confidence of the questionnaire are detailed in Table 5.

It should be noted that the value of Alpha equal to or greater than 0.7 is considered an adequate internal consistency of the instrument GONZÁLEZ ALONSO; PAZMIÑO SANTA CRUZ, 2015). In the analysis of all the items, a 0.943 of reliability was achieved according to Cronbach’s Alpha. However, the planning dimension of teaching is the only one with a reliability range slightly below 0.7, which does not affect its consistency.

As a complement, a Kendall’s T correlational analysis (PÉREZ JUSTE et al., 2009) was applied to verify and reinforce the reliability measurements using SPSS software, version 22. The correlations by dimension are presented in Table 6.

The results of the Kendall correlational test are summarized below:

In summary, the study of Kendall’s intra-dimensional correlations reinforces the levels of reliability found with Cronbach’s Alpha.

In addition, an exploratory factorial analysis was performed using SPSS software version 22. This type of analysis allows to establish a greater precision on the latent and observed variables or constructs (LLORET-SEGURA et al., 2014). Therefore, it seeks to establish whether there are matches between the factorial analysis and the dimensions defined a priori in the study.

As the first statistical sufficiency test, it was observed that the Kaiser-Meyer-Olkin (KMO) measurement analysis and the Bartlett sphericity test showed very positive values, between 0.920 and 0.000 ³, so that exploratory factor analysis is feasible (Table 7).

Considering the results of this first test, a second analysis is carried out on the basis of the following criteria:

These results indicate that these seven factors explain 61.6% of the total variance, which allows to describe the teaching experience in the teaching process and learning in schools in remote education (Table 8). It should be noted that an appropriate model is considered when aggregations of the extracted factors exceed 50% of the variance explained (FLORA; LABRISH; CHALMERS, 2012).

The identification of factors and their influence on the total variance explained is presented in Table 9.

With respect to the dimensions defined in the original study design, there is a medium agreement with the factors found. The most relevant areas according to the factorial analysis are: The items linked to didactic resources (Dimension C), pedagogical support (Dimension F), interpersonal relations (Dimension D) and evaluative processes (Dimension E) indicated in Table 5.

Regarding the two open questions on facilitators and hinderers, these have a very high degree of validation by expert judgment (^{ESCOBAR-PÉREZ; CUERVO-MARTÍNEZ, 2008}), since they delve into particular components of these areas associated with technological access, training in digital competencies and curricular-evaluative innovation processes, which allows us to maintain that they have consistent content validity.