Starting from 1307 total articles, this cluster identified 819 initial papers, 537 of which were reviewed due to duplicate publications. A total number of 10 articles was finally included (Table 2).

 

As for the sample, five studies recruited students as research participants (one from preschool, two from a junior high school, and two from a senior high school), three sampled staff (two targeted school leaders and one head teachers, teachers, and other related staff), and another two studies sampled both students and teachers.

 

Concerning the study design, the ten papers of this cluster present different methodologies (see Table 1). In five studies, effects of school building and architectural features were investigated using quantitative methods (surveys), whereas the remaining five studies used qualitative methods (field and case studies, observational designs, interviews). One study [57] used a causal comparative research, with a pre-post-test design comparing homogenous groups (elementary, middle, and high school students) tested before and after exposure to the intervention of interest (e.g., school building renovation).

 

As regards the measures, the initial search found either self-report or objective measures of effects of school building design on school users, and only one study using objective measures was identified [57], specifically students’ scores at mathematics and reading subtests. Other studies used either one or more of the following types of self-report measures: Teachers’ and/or students’ evaluation of learning environment (three), educational behaviors (two), design quality and school usability (two), wellbeing (one), and aspirations for the future (one). The most studied outcome variable was learning evaluation (i.e., students’ achievement and performance), whereas student drop-out rate was not examined in result studies.

 

As for the countries, the studies were mostly (70%) conducted in Europe, specifically two in the UK (20%) and the others in other different European countries. The remaining three (30%) studies were conducted in North America (two) and Asia (one).

 

Considering the outcome variables, the results reveal that 61.5% of the reviewed studies of Cluster 1 presented positive (+) results, 30.8% presented negative (−) results, and 7.7% presented no change (0). For example, the study of Cencič (2017) showed that the age of the school building (new, old, or renovated) has a different effect on school leader evaluation of learning environment, with new schools scoring higher than old or refurbished schools in some factors (e.g., ecology, feelings, aesthetics), and old schools scoring higher than new or refurbished schools in other factors (e.g., logic, mathematics, creativity).

 

Overall, this analysis highlights some strengths of this line of research. First, the literature on the effects of school building and architectural design integrates studies carried out with different methods and approaches (i.e., qualitative and quantitative) and involving different users (ranging from students at different grades to teachers and staff members). Moreover, these prior studies investigated the role of rebuilding and architectural features on several aspects of the life at school such as teaching experience, learning outcomes, satisfaction.

 

However, these results also underline some gaps that future studies should address. More specifically, the research showed some inconsistent or not conclusive evidence about the positive effects of renewing and rebuilding schools. Thus, to better explore the phenomenon, further investigations could take into consideration crucial moderators (e.g., place identity, gender). Importantly, most of these studies were conducted on a small number of participants, using different measures and focusing on different design and architectural aspects: If on one side the integration of different tools and perspective enriches the analysis, on the other side the comparison of results is not always possible. Therefore, additional studies should be carried out to fill this gap, taking into account the holistic nature of environmental aesthetics that requires—much more than other aspects—a bridge between complementary perspectives [58].

Starting from 1307 total papers, this cluster identified 181 initial articles, 126 of which were reviewed due to duplicate publications. A total number of 22 articles was finally included (Table 3).

 

About the sample, 17 studies (77.3%) recruited only students as participants (of which six of primary schools, two of middle schools, four of both primary and middle school, four of post-middle school and one of unspecified age) and the remaining five studies sampled both students and teachers (22.7%).

 

As for the study design, different methodologies were used across the 22 papers of this cluster (see Table 1). In 19 studies (86.4%), effects of indoor environmental features were detected by quantitative methods (i.e., survey, experiment, and field studies), two studies (9%) used a mixed design (both quantitative and qualitative methods), and the remaining one study used qualitative methods (collection of the teachers’ data).

 

As concerns the measures, 10 studies used objective measures (e.g., classroom ventilation rates, acoustic and lighting parameters, students’ scores on standard tests), whereas three studies used one or more of the following types of self-report measures: Teachers’ and/or students’ evaluation of teaching/learning experiences, perceived satisfaction, thermal sensation/comfort, and so on. The remaining nine studies used both objective (especially to assess exposure conditions, in terms of role of acoustic and lighting features of the classroom environment) and self-report measures. The most studied outcome variable was students’ learning, in terms of performance, ability, level of attention and concentration, followed by wellbeing in terms of health and comfort, and, finally, by students’ and teachers’ perceptions of physical environment. Regarding the countries, the studies were mostly (63.7%) conducted in Europe (eight) and US (six), while the other studies were conducted respectively in Asia (five), Australia and New Zealand (two), and Africa (one).

 

The overall findings show that 46.7% of the reviewed studies presented positive (+) results, 50% showed negative results (−), and 3.,3% presented no changes (0).

 

Indeed, differently from the prior cluster that identified an equal number of qualitative and quantitative studies, the present cluster of studies was skewed toward the quantitative and experimental approach. This is probably due to past research traditions on the effects of physical attributes that are more prone to environmental assessments. Although this approach has some concrete advantages (e.g., identification of the variables, involvement of a greater number of participants, comparison between studies), on another hand, it overshadows important aspects. For instance, this line of research often investigates the effects of environmental features on “objective” variables such as learning outcomes and performance: Qualitative research would be likely to deepen the analysis on subjective users’ wellness, experience of stress, or comfort. Moreover, most of the cited studies focused on a single physical characteristic of the indoor environment (e.g., noise, light, ventilation), leaving out important interactions between these features in a naturalistic setting and between indoor and outdoor or contextual variables.

 

In this vein, studies on multisensory integration (e.g., light color and temperature; [59]) could provide important suggestions for future research. Importantly, few studies explored the effects of indoor physical attributes (e.g., [60]) on pupils with special needs: Developing this line of research is crucial to design actual inclusive learning environments.

Starting from 1307 total articles, this cluster identified 108 initial papers, but only 81 were reviewed due to duplicate publications. Twelve articles were finally included, of which three studies came from other clusters (Table 4).

 

As for the sample, five studies (42%) recruited participants from students (specifically, from elementary schools), three (25%) sampled staff (among teachers, school administrators, and other related staff), and the remaining four studies sampled both students and teachers (33%).

 

As regards the study design, a range of different methodologies were used amongst the 12 studies in the third cluster. In eight studies (about 66%) effects of spatial features (classroom design) and furniture were measured by qualitative methods (focus groups, informal interviews, observations, case studies, reports), two studies (about 17%) used quantitative methods (i.e., surveys and field studies) and the remaining two studies (about 17%) used a mixed design (both quantitative and qualitative methods).

 

Concerning the measures, 11 studies used self-reported measures (i.e., students’ perception and satisfaction towards the learning environment, in terms of spatial evaluation of movement, furniture arrangement and room design, subjective comfort, wellbeing), whereas only one study (see [61]) used both objective and self-reported measures.

 

About the countries, four studies were conducted in Europe (two in England, one in Ireland, and one in Portugal), two studies were conducted in Asia (one in Turkey and one in Sri-Lanka), four studies were conducted in the American continent (three in USA and one in Brazil), and finally, two studies were conducted in a not specified country.

 

The overall findings illustrated that 75% of the reviewed studies presented positive (+) results, whereas the remaining 25% showed negative (−) results.

Overall, the research literature on this cluster has been definitely characterized by the predominance of qualitative data, collected through interviews (individual or group ones) or observations, or derived from the realization of case studies. The primacy of self-report measures as outcome variables is another distinctive feature of this cluster. The presence of studies addressing the needs of specific students’ categories (in particular children from primary schools, but also deaf or autistic students) could be related to the fact that the spatial level of analysis of this cluster is more circumscribed and focal than the others, representing a sort of microsystem for the user, as highlighted by the multiplace approach (see [7,38,39]. In other words, the classroom environment being the most direct, central, and thus meaningful subsystem of the school environment in the experience of students and teachers, then this spatial level should be particularly cared for in order to respond to differential needs.

 

As for the previous clusters, it is quite difficult to make comparisons across studies, given the predominance of qualitative studies as well as the high variability in construct operationalization, sample size and characteristics, kinds of techniques and tools (often ad hoc ones, not previously validated). Future research should investigate the potential role of socio-demographic variables (e.g., gender) and socio-psychological dimensions (e.g., interpersonal distance, intra-group and inter-group dynamics, social norms) as potential moderators of the relationship between the “objective” classroom environment features and users’ responses.

Starting from a total of 1307 papers, this cluster identified 199 initial articles, 143 of which were reviewed due to duplicate publications. Twenty-four articles were finally included, one study of which came from another cluster (Table 5).

Concerning the sample, seven studies (29%) recruited participants who were students (one of which was attending early childhood education, four of which were attending primary school, one from middle school, and, finally, one with a sample of primary school students and another sample of high school students), nine studies (38%) sampled staff (among teachers and/or school principals) and/or other local members (parents, careers, charity staff), and the remaining eight studies sampled both students and teachers (33%).

 

As regards the study design, a range of different methodologies were used. In 18 studies (76%), effects of the presence of school activities in outdoor education form were measured by using qualitative methods (multi case studies, field experiments, semi-structured individual/group interviews, observation, and focus groups), four studies (17%) used quantitative methods (survey, experimental, and quasi-experimental studies), and the remaining two studies (8%) used a mixed design (both quantitative and qualitative methods).

 

About the measures, all studies used self-report measures (i.e., students’ and teachers’ perception of impact of outdoor education on learning, involvement, and enjoyment of participants), six of these used also objective measures (i.e., science knowledge assessment, knowledge test scores, students’ academic performance).

 

As for the countries, 50% of studies were conducted in North America, 33% of studies were conducted in Europe (three in England, one in Scotland, one in Wales, one in Slovenia, one in Italy, and one in Croatia), and the remaining 17% of studies were conducted in Australia (two) and Asia (two).

 

Most of the findings (89%) presented positive (+) results, whereas the remaining 11% showed negative (−) results. The most examined outcome variable was learning evaluation, which referred to both the physical activity and the outdoor teaching experience.

 

Overall, if compared to the previous ones, this cluster of studies fruitfully integrate different perspectives and methodologies, revealing a quite consistent pattern of results: The opportunity to use outdoor spaces and facilities for outdoor teaching proved to be positively related to a wide range of variables. Importantly, these outcomes are not exclusively referred to performance in curriculum activities but also to relevant social skills (e.g., positive relationships, friendship, independence, self-confidence). However, these results also underline some points that require more attention and indicate future avenues of research. First, as for the previous clusters, outcome variables related to the outdoor environment have been often assessed through ad hoc measures: Further studies should address this point trying to validate more reliable instruments. This would also facilitate the comparison between different studies and results, thus providing a more systematic picture of the phenomenon. Second, research should try to integrate the investigation on indoor features with that on outdoor variables. Indeed, the relation between indoor and outdoor environments (hallways, windows, French window opening into the garden) has been barely explored. Furthermore, future studies should focus attention on individual differences that are likely to moderate such effects, as gender, age, and specific needs.