Previous research has found that students’ previous school experiences will influence the way they face the current educational situation. Continued poor performance and negative performance feedback produce frustration and may consequently affect future outcomes (Weiner, 1986).

Based on Expectancy-value theory, Gorges and Kandler (2012) found that adults’ appraisal of a new learning opportunity is influenced by previous learning experiences at school, specifically by expectancy of success (self-concept), value (interest), and affective memories. They conclude that “school experience is an antecedent of adults learning because experiences and values stabilize over time” (p. 612). According to the attribution theory, students’ own perceptions or attributions regarding to why they succeeded or failed at the school determine the amount of effort they will engage in school task in the future.

In sum, students’ initial perception of the current T–L process may be conditioned by previous academic experiences or by the information that students already have about the teacher. It is expected that a background of success will contribute to a more positive perception than a background of failures. Similar reasoning is also plausible for teacher’s initial perception.

Based on these assumptions and findings, we defend that the variables which refer to student success and failure attributions, as well as affective memories about past academic experiences, should be taken into account. The same recommendation can be made for teachers.

Based on the Job Demands-Resources Model (JD-R) (Demerouti et al., 2001; Bakker and Demerouti, 2007), the learning context refers to the perception which the teacher and students have formed of the educational setting in terms of demands and supports/resources. Demands can become stressing if they require a great deal of effort for the subject to achieve it. Subsequent research (Lorente et al., 2008) has the need to consider both job and personal resources to amplify the model’s explicative capacity. Adapting and applying the JD-R model to the school context implies identifying what the specific demands and resources are for teachers and students in the school context. The learning environment quality depends to a great extent on the simultaneous presence of environmental challenge (basically through educational demands) and the environmental support provided (Shernoff et al., 2016). One way of create a challenging classroom environment is designing novel and attractive demands.

According to the Job Demands-Resources Model (JD-R) (Demerouti et al., 2001; Bakker and Demerouti, 2007), job demands “are physical, psychological, social or organizational aspects of work that require physical and/or psychological effort (cognitive or emotional), and are associated with a certain physiological and/or psychological cost” (Bakker and Demerouti, 2007, p. 312). Demands can become stressing if they require a great deal of effort for the subject to meet them. When applying this theory to the school context, we consider that the demands that are difficult to be perceived by students to pass a specific subject may affect their level of stress and engagement (the same reasoning is also plausible for teacher demands). A moderate difficulty of demands, not too high, not too low, is recommended. According to Vygotsky’s theory, the degree of difficulty of a specific task (or demand) should be in the “zone of proximal development (ZPD),” which means that with the assistance of a more capable person, a child is able to learn skills or certain aspects of a skill that go beyond the child’s actual developmental level. The demands that students have to meet (studying demands) in order to pass a specific curricular subject (e.g., problem solving, assignments, oral presentations, lab work, study planning, etc.) are detailed in the subject’s planning and are subordinated to fulfill learning objectives. Students can obtain information about their required demands at the beginning of the course, mainly when the teacher introduces and explains the subject’s planning. The information from the evaluation system, such as tasks to do, level required to pass the subject, evaluation criteria, etc., is especially relevant for students.

Similarly, demands under teacher responsibility and their perceived difficulty may also influence teacher stress or engagement depending on their level of difficulty because, as we state before, demands can become stressing if they require a great deal of effort for the subject to meet them. The demands to be met by the teacher derive basically from the State’s Education Project, the District School Council and the school’s policy.

According to The Job Demands-Resources Model (JD-R) (Demerouti et al., 2001; Bakker and Demerouti, 2007), job resources refer “to those physical, psychological, social, or organizational aspects of the job that may reduce job demands and the associated physiological and psychological cost, are functional in achieving work goals, and stimulate personal growth, learning and development” (Hakanen et al., 2006, p. 497). When applying this theory to the school context, we assume that the perception of the supports/resources that the teacher and students are expected to be provided with to meet the required demands will influence their level of motivation and engagement. Thus supports/resources for teachers make their teaching work easier and help them to be more efficient to fulfill the stipulated instructional objectives (teaching demands). Conversely, the barriers/obstacles perceived by teachers not only prevent/hinder them from fulfilling the required objectives (teaching demands), but also cause them stress and burnout (Blase, 1982; Doménech and Gómez-Artiga, 2010).

Following the classification proposed by Schwarzer and Greenglass (1999), support can be internal or external. Internal support refers to students’ (e.g., self-efficacy) and the teacher’s (e.g., professional development) personal resources, and it will be treated in the following subsection. External support comes from the workplace, basically from administrative, social and didactic resources. Administrative support for teachers comes from school administrators (e.g., District School Council, supervisor, principal, etc.). Social support may come from either inside or outside the school. Referring to inside the school, supports for students come from teachers, peers, etc., whereas supports for teachers come from colleagues, psychologists, etc. Referring to outside the school, supports for students basically come from family and friends, whereas supports for teachers come from family and partners. Didactic resources refer to learning tools for students that are provided by teachers (e.g., computers, books, videos, etc.), as well as teaching tools for teachers (e.g., digital blackboard, computer, software, etc.) and school facilities (e.g., labs, library, gym, offices, etc.).

As seen above, external support comes basically from the classroom and family context. Instead, internal support refers to students’ and the teacher’s personal resources.

Generally, the Job Demands-Resources Model (JD-R) (Demerouti et al., 2001; Bakker and Demerouti, 2007) was used to explain employees’ work conditions in terms of demands and resources, and how these conditions relate to positive (e.g., engagement) and negative (e.g., stress and burnout) outcomes. Applying and adjusting the JD-R model to the school context implies identifying what the specific demands and support/resources are for teachers and students. Centered on students, supports/resources for students facilitate their learning and help them to fulfill the stipulated learning objectives (the major demand) and the other subordinate demands (studying demands) required to fulfill learning objectives. The main student supports come from the classroom and family context. According to Shernoff et al. (2016), the learning environment quality depends, to a great extent, on the simultaneous presence of the environmental challenge (reflected basically through educational demands), and on the provided supports (Shernoff et al., 2016). Students’ beliefs about themselves and their environment influence their motivation (Lin-Siegler et al., 2016). In order to examine students’ beliefs about themselves and their environment in terms of demands and supports/resources, we classified the perceptions that students make of demands and support variables into two orthogonal bipolar axes. One axis ranges between high supports-low barriers (the positive pole) and low support-high barriers (the negative pole). The other axis ranges between attractive-meaningful demands (positive pole) and unpleasant-meaningless demands (negative pole). The latter axis indicates to what degree demands connect with students’ interests, needs and academic level (meaningful vs. meaningless), and to what extent demands activate students’ curiosity (attractive vs. unpleasant). Based on the above rationale, we hypothesize that the perception of demands and support variables at the beginning of an instructional segment (e.g., task, theme, course, etc.), in terms of demands and support/resources, will predict students’ intention to learn. The conceptualization of intention to learn will be explained in the next sections. The formulated predictions are represented more specifically in Figure 2. As can be seen, quadrant I predicts the maximum activation of intention to learn; in contrast, quadrant III predicts the minimum activation of intention to learn. High difficult demands predict an expected stressful process during the course. Finally, we wish to point out that the perception of demands and support variables can also be influenced by prior academic experiences viewed by students in either the same educational setting or similar precursor courses (e.g., same subject, same teacher, etc.). A background of success will contribute to the perception of positive demands and support variables; in contrast, a background of failures will contribute to a negative perception. How the supports/resources and demands for teachers are related to intention to teach is currently under study.

This construct is based on the assumption that the degree to which students’ believe that a subject or a task is worth pursuing is a key component for understanding students’ behaviors and learning outcomes (Liem et al., 2008). Although this concept seems relatively simple, it is not so because it has many conditioners. An object can have an intrinsic, extrinsic and instrumental value (as a step to fulfill a longer term goal). Eccles et al. (1983), Eccles and Wigfield (2002), and Eccles (2009) distinguished four components of task-value: attainment value, intrinsic value, utility value, and cost. They defined attainment value as the personal importance of doing the task well. Intrinsic value is the enjoyment that the individual gets from performing the activity (related to process expectancy). Utility value is determined by “how well a task relates to current and future goals, such as career goals” (Eccles and Wigfield, 2002, p. 120). Finally, these authors identified cost as a critical component of value, which was conceptualized as a negative determinant in engaging in a task due to, e.g., performance anxiety, fear of both failure and success, and the amount of effort needed to succeed (Eccles et al., 1983; Eccles and Wigfield, 2002). Prior studies (Cole et al., 2008) have found that students who perceive high task values make a greater effort and achieve more than those students who perceive low task values. In the same vein, Miller and Brickman (2004) argued that students only make their best effort and spend a substantial amount of time on mastering an academic task if they perceive it to be important and useful for them in the future.

This concept is related to students’ (and the teacher’s) wishes, hopes and desires. If from the beginning of the course students (and the teacher) predict that their wishes, hopes and desires are going to be met in the current educational situation, they will transform them into goals (learning goals). Bandura (1993) argued that most human motivation is cognitively generated. “People motivate themselves and guide their actions anticipatory by the exercise of forethought” (p. 128). Bandura (1987) also indicated that the two basic capacities that largely explain human behavior are their prediction and self-regulation capacity. Individuals predict the consequences of future actions through prediction capacity. This capacity allows people to feel motivated and to regulate their actions in advance (self-regulation). Predictions can be associated with underlying motivational processes (Bandura, 1987). Motivational processes are activated by the learner (and the teacher) with a specific subject at the beginning of the course. Table 2 shows the anticipatory cognitive motivators that we have selected for the MOCSE model and are suggested to be evaluated at the beginning of the course, after some days/weeks of class.

Centered on students, this action is headed by the following question: What is my objective/purpose in this subject?, the answers lead to the “Achievement Goal Theory” (Dweck and Legget, 1988; Nicholls, 1989; Ames, 1992; Wigfield and Eccles, 2000). This theory posits that “the purposes that students hold for engaging in a specific academic task (i.e., their achievement goals) are an important antecedent to their achievement-related processes and outcomes” (Liem et al., 2008. p. 487). Thus, the Achievement Goal Theory (Dweck and Legget, 1988; Nicholls, 1989; Ames, 1992; Wigfield and Eccles, 2000) is proposed to explain and operationalize this dimension. Three types of achievement goal that have been usually studied are mastery, performance-approach and performance-avoidance (Skaalvik, 1997; Midgley et al., 2000). Those students who adopt a mastery goal focus on improving their competence and progress in an academic task/subject. The students who adopt a performance goal are concerned about the demonstration of competence shown by others. The students who adopt performance-avoidance goal wish to avoid social judgments and humiliation. The above classification can be completed with two more types of goals introduced by Alonso Tapia (2002) named self-worth and social recognition goals. Students who adopt the former want to get proud of their own performance. Students who adopt the latter type wish to obtain social recognition from others, such as teacher, parents, etc. Based on the two classifications exposed above, we have distinguished three broader groups of achievement goals according to two parameters: type of motivation (intrinsic vs. extrinsic) and type or reinforcement (positive vs. negative). Type I goals, based on intrinsic motivation. In this case the most important point for students is to improve their skills and progress (e.g., mastery goals or self-worth goals). Type II goals, based on extrinsic motivation and positive reinforcement. In this case the most important concern for students is to demonstrate their competence in obtaining social recognition or another reward (e.g., performance goals). Type III goals, based on extrinsic motivation and negative reinforcement. In this case the most important point for students is to avoid humiliation and embarrassment, and to protect their self-esteem (e.g., performance-avoidance goals). According to King and Mclnerney (2014) mastery and performance goals differ in terms of how competence is defined. “Students who pursue mastery goals define competence through interpersonal standards, while those who pursue performance goals define competence through normative comparisons with others” (p. 43).

Finally, there is also the possibility that some students do not pursue any of the aforementioned goals. This occurs when students are not motivated to learn and make the minimum effort, or even try to avoid learning, which reflects passivity or inaction. Work avoidance represents the absence of an achievement goal (Elliot, 1999). For a more extensive description, see the study conducted by King and Mclnerney (2014), who examined the structure, antecedents and consequences of the avoidance goal construct.

To summarize, two main ideas are pointed out. First, the maximum activation of intention to learn is achieved when students believe that the subject is worth pursuing, make positive forecasts and adopt domain-focused goals. The main objective of these students is to master the subject, to learn and to progress. They are characterized by taking on difficult challenges, by striving to learn, and by getting actively involved (active coping) in the T–L process. Second, we use two dimensions to evaluate intention to learn (or motivation to learn), (a) the first dimension indicates the subject worth pursuing and chances of fulfillment, (b) the second dimension indicates the achievement goal-setting; i.e., the goals adopted by students. Students may be motivated to master the subject, obtain reinforcement, get good grades, demonstrate their worth, etc. Our proposal of the relationship expected between anticipatory cognitive motivators and goals is displayed in Table 3.

If we simultaneously consider both intention to teach and intention to learn, as they really take place in the classroom, any of the following basic possibilities could happen: (a) teacher’s teaching intention is optimal (high activation); (b) a teacher’s teaching intention is poor (low activation); (c) students’ learning intention is optimal (high activation); (d) students’ learning intention is deficient (low activation). To undertake a T–L quality process, it is necessary, but not enough, for intention to learn and intention to teach being optimal (see Table 4). The quality concept is explained in detail in the next section.

Finally, we wish to put forward some important ideas before ending this section.

In short, the first two components of the model (appraisal phase and intention activation), plus the educational action plan, represent the pre-actional decisional phase, and are responsible for learner and teacher decisions about how to deal with a new educational process. Students decide in this phase if they first want to engage in order to master the school subject or not. So we call the variables from components 1 and 2 “predictive variables” because they are able to predict students’ engagement from the beginning of the course (Doménech, 2006, 2011a; Doménech et al., 2014; Abellán, 2016).

Basically, there are three time points when the agents involved in the learning-teaching process make important decisions about the course, which are also known as macrodecisions (microdecisions are made about the theme or task). The most important time point is the period at the beginning of the course, but the time points that correspond to the second and third trimesters are also important (in Spain, school courses last three terms, and each term lasts 3 months). The decisions made at these two time points are mainly triggered by knowledge about a new element: the results that students obtain when they end each trimester, which are provided on a report card.

Active learning is usually defined by authors as the learning that requires students engaging cognitively and meaningfully with materials (Bonwell and Eison, 1991) to get involved with the information presented (analyzing, summarizing evaluating) rather than just passively receiving it (King, 1993). According to this conceptualization, active learning is understood as “cognitively engaged.” However this term (active learning) has also been considered as a multifaceted construct, from motivational, behavioral and emotional perspectives (Chi and Wylie, 2014; Fredricks et al., 2004). From a motivational perspective, active learning focuses on either the precursor attitude or the interest in getting involved in learning tasks. From a behavioral perspective, active learning focuses on student actions, such as how often students attend class or do their homework, etc. Finally from an emotional perspective, active learning focuses on affective reactions to teachers, peers, etc. In the current work, active learning is used as cognitive and behavioral engagement. Taking Lazarus and Folkman’s (1984) theory as a reference, it is plausible to consider that if students and the teacher perceive a stimulating and supportive environment, they will wish to get engaged (cognitively and behaviorally) in the T–L process, and will consequently develop active coping strategies that focus on the problem (e.g., seeking social support, confronting the problem, etc.) that aim to manage/overcome any problems and challenges that may arise. On the contrary, if they perceive a threatening environment they will wish, mainly, to protect themselves from negative emotions, and will therefore very likely develop passive strategies that focus on emotion (e.g., escape-avoidance, distancing, etc.). It would be desirable for both students and teachers to adopt active coping strategies (problem-focused coping), engaging and striving to overcome the problems or challenges that may arise throughout the educational process. Teachers can promote active learning by creating a more active learning environment (Bonwell and Eison, 1991; Fink, 2013) by, for example, designing significant lessons and activities that overcome passive learning. The ICAP framework (Chi and Wylie, 2014) provides guidelines for teachers as to how to promote active learning.

A T–L process is considered efficient when it provokes the most marked transformation possible in students in their cognitive and socio-effective domains. This will be possible if the psycho-educational principles and specifications derived from the empirical research proposed by the literature are followed by teachers and students. The principles and specifications capable of facilitating learning were interpreted basically in terms of demands and supports/resources. Teacher support contributes to maintain student “executive motivation” which, in turn, affects learning outcomes. Demands for students are related to learning objectives, tasks and contents. Demands must be assumed by students who, besides teacher support, also need to apply effective strategies to accomplish the required demands (“getting things right the first time”), all of which subordinate to achieve learning objectives. Therefore, effective actions and strategies from the teacher and students are needed to meet learning objectives. The transformation achieved by students during the T–L process conducted in a specific subject matter can be operationalized by calculating the difference between the students’ starting point in the pre-instructional phase (students’ initial state) and the post-instructional phase (students’ final state).

It is important that the teacher enjoys teaching and that students enjoy learning. This means having to focus on the process as much as on the results, or even more. When focusing on the educational situation as a stage where the T–L process takes place, it is important to study and identify the process elements that could affect (positively or negatively) the psychological health of teachers and students. Traditionally, the research carried out in this field has focused more on studying negative emotions (teaching discomfort, stress, burnout, etc.) rather than on positive ones. However, this approach has changed in recent years with the rise of positive psychology.

From the psychological point of view, we understand a healthy educational process as one that produces in agents or participants (the teacher and students) positive emotions; on the contrary, if the emotions experienced by the involved subjects are mostly negative, it is considered an unhealthy process (be aware that triggers can also originate from the external contexts directly connected to the educational situation, such as family and school).

Teaching is highly emotional work (Marchesi, 2007) given the constant interactions among the three key elements (teacher, content and students) throughout the T–L process. Based on MISE, we particularly stress the importance of the Personal Interactions dimension (dimension three) as most of the emotions experienced by the agents involved (the teacher and students) are activated in this phase. Based on the Control-Value Theory of Achievement Emotions (Pekrun et al., 2007), we must take into account the processes of “appraisals control” (efficacy beliefs, expectations, and responsibilities) and “value appraisals” (perceived task value and results) since, according to this theory, they are important antecedents of achievement emotions. A healthy educational process will provide well-being for the teacher and students which, in turn, will affect the quality of education. Finding the instructional keys that can contribute to teacher and student well-being is a challenge that we are currently working on. Measurement instruments assessing students’ achievement emotions are provided by Pekrun and his colleagues (see Pekrun et al., 2005, 2011).

Three main actions, under teachers’ responsibility, should be undertaken during the course to improve learning outcomes and student-teacher satisfaction.

The same procedure and actions can be implemented at the school level. Previously, teachers should be trained in how to use the MOCSE model in the classroom. The empirical data obtained through MOCSE procedures can provide the scientific basis to design effective programs for schools adapted to different levels of education and subjects. It is also a useful tool that can be employed by policy makers and educational leaders to design prevention and intervention programs to increase learning outcomes and satisfaction at schools.