**1. Introduction**

Small and medium-sized enterprises (SMEs) are considered a source of economic growth and are seen as a key sector for creating employment in many countries around the world. Consequently, training and learning are considered critical to SMEs' growth in many countries. To this end, references [1, 2] consider that in knowledge-based economies, a firm's investment in training and updating its employees' skills is a key element of its growth. However, SMEs do not provide sufficient training mainly because they cannot spare time for employees to

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

attend external training programs and because internal training is too expensive. Therefore, SMEs should logically turn to e-Learning to provide training as the benefits associated with it are supposed to solve these problems. But the logic is not working. SMEs have not rushed to embrace e-Learning in order to train their employees. Why? What are the barriers and constraints they face?

In Canada, particularly Atlantic Canada, SMEs have played an important role in the economic development in various ways and their contribution towards a healthy economy has been recognized. They are defined as businesses having fewer than 500 employees and they represent the majority of businesses [3]. They are the fastest growing segment of the economy, and are considered the foundation of economic development [3–5]. Due to their great flexibility and adaptability, they represent the economy sector that creates the most employment [3, 6] and they remain critical to the economic prosperity of the region as in other parts of the world [see, for example, 7–9]. Yet, despite their great contribution to the region's economy, there are very few studies on them and even less on the training barriers they face, and this despite the fact that the most successful economies are those with the best trained individuals [1, 2, 10].

Capability development of small and medium firms remains critical to economic prosperity in Atlantic Canada as well as in other parts of the world [for example, see 3, 5, 7–9,11–13]. It is therefore important to know the barriers faced by SMEs regarding training, more specifically e-Learning, in order to be in a position to help them ensure their growth and their sustaina‐ bility.

The purpose of this study is descriptive and prescriptive. After having identified the barriers and constraints SMEs experienced when they wanted to use e-Learning using a survey of the literature on the issue, the first objective is to determine through multiple case studies if the barriers to e-Learning actually experienced by SMEs in Atlantic Canada are still the same after all these years. If so, the second objective is to introduce possible solutions to assist SMEs in surmounting these barriers.

Thus, the remainder of this chapter is arranged as follows. Section 2 presents the method used for the study. Section 3 presents a literature census on the various barriers and constraints to the use of e-Learning by businesses. Section 4 determines through multiple case studies the barriers and constraints to e-Learning actually encountered by SMEs in Atlantic Canada and proposes different approaches to overcome those barriers. The conclusion and discussion will be included in section 5. The references are in section 6.

### **2. Method**

Given the present state of knowledge on training in SMEs and on e-Learning, the method used for this study includes a census of the literature on training and e-Learning combined with a qualitative and exploratory research approach, i.e. multiple case studies. The literature census covers more specifically the barriers and constraints businesses faced when they wanted to use e-Learning. The case study method is well adapted in situations where theoretical propositions are few and field experience is still limited [14]. Multiple-site case studies allow one to understand the particular context and evolution of each firm in regard to e-Learning. Sixteen SMEs located in the Atlantic Region of Canada were studied in 2006, four in each of the provinces of New Brunswick, Nova Scotia, Prince Edward Island and Newfoundland. In 2012, 6 years later, four other SMEs located in New Brunswick and Prince Edward Island have been studied to verify if the businesses were still encountering the same problems in regard to e-Learning. These 20 businesses were selected because they were sufficiently successful (at least 10 years in business) and representative in terms of industry and size, for theoretical generalization purposes. These manufacturing SMEs stem from various sectors such as: construction, textile, oil and gas, pulp and paper and processed food sector. Following North American research [4, 15], a small enterprise (SE) is defined as having 20 to 99 employees, whereas a medium-sized enterprise (ME) has 100 to 499.

Data were collected through semi-structured tape-recorded interviews ranging approximately 2 hours each with the owner-manager or CEO and with the firm's HR manager or manager responsible for training. E-Learning users were also interviewed. The interviews consisted of a series of standardized open-ended questions related to e-Learning. The standardized openended interview, as explained by reference [16], is a structured approach in which participants are always asked identical questions designed to generate an open-ended response. This approach was utilized to solicit a variety of viewpoints based on individual experiences, but also to control researcher biases. All narrative interviews were transcribed, coded and analysed using open line-by-line coding to identify themes following reference [17] prescriptions with the assistance of the Atlas.ti application. For confidentiality reasons, fictitious names of individuals and firms participating in the study were used. For example, the first business interviewed is represented by the letter A, and a name starting with the letter A (Arthur, Andy) is given to the representatives of this business. The second business interviewed is represented by the letter B, and a name starting with a B (Bert, Bob) is used and so on. As presented in the research results section, these firms range in size from 60 to 490 employees and operate in industries whose technological intensity varies from low to high. All export except for one firm (M). The SMEs interviewed in 2006 were regrouped in four e-Learning profiles of increasing intensity based on the extent of their awareness and use of e-Learning (none, weak, average, strong). The four businesses interviewed in 2012 are grouped together, but not based on their e-Learning profiles of awareness and used of e-Learning. Three of these businesses were using e-Learning, and one was not.


**5. Conclusions**

In conclusion, among patients with generalized convulsive SE requiring MV, half had criteria for aspiration syndrome and one-quarter of patients had a BAP. Clinical characteristics and biomarkers, such as serum CRP, PCT, and albumin levels measured during the first 24 h, were not useful to differentiate BAP from pneumonitis. Up to onequarter of bacteria isolated from tracheal samples were not sensitive to ACA, with no clinical consequences despite inappropriate antibiotic therapy. BAP tended to be associated with poor functional outcome and death at 3 months. Our results highlight the need for a method to rapidly differentiate pneumonitis from BAP, such as PCR-based techniques.

**Supplementary Materials:** The following supporting information can be downloaded at https: //www.mdpi.com/article/10.3390/jcm11226673/s1, Table S1: Comparison of patients with BAP according to amoxicillin/clavulanic acid susceptibility among causative pathogens.

**Author Contributions:** Conceptualization, R.T. and S.N.; methodology, R.T.; validation, R.T., F.W. and S.N.; formal analysis, R.T. and S.N.; data curation, R.T., F.W. and P.D.; writing—original draft preparation, R.T.; writing—review and editing, R.T., F.W., P.D. and S.N. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding.

**Institutional Review Board Statement:** The study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of SRLF (French Society of Intensive Care) (protocol code CE SRLF 21-38 and date of approval: 3 September 2022).

**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.

**Data Availability Statement:** The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy reasons.

**Conflicts of Interest:** S.N. received payment for lectures from MSD, Pfizer, Gilead, Biomérieux, Bio Rad, and Fischer and Paykel. R.T., F.W. and P.D. declare no conflict of interest.


**4. Soil N availability and other plant nutrient availability enhancement**

Nitrogen plays an important role in yield determination when relatively adequate levels of other agricultural factors exist. Continued use of inorganic fertilizers has not only altered the soil p H, soil structure, and texture, but has also disrupted niches for micro- and mesofauna, which are essential for nutrient recycling [49]. Alternatively, under systems of organic farming management, when industrial N fertilizer is not used, organic matter origin-N, after biological degradation, is converted into mineral N forms, ammonium and nitrate, and becomes a major factor in plant production. However, as the mineral N content in soils increases beyond the capability of plants to take it up, it will cause N leaching and increase other kinds of N losses into the environment. In this case, it is important to understand the N cycle and soil N balance within an agroecosystem.

As common knowledge, the origin of all kinds of N is air N2, 79% by volume of the earth's atmosphere. Soil microorganisms, free-living or associated with legumes, fix atmospheric N. This complex biological process begins with air N and ends with organic N. After organic matter decays, NH4 + , which is ready to be used by higher plants, is released. NH4 + can be converted into NO3 – by nitrifying bacteria and generally most NH4 + is modified into NO3 – in the soil. Thus, over 90% of soil N is typically NO3 – , not NH4 + , although NH4 + can be formed from NO3 – through the process of denitrification in soils [50].

The denitrification process starts with NO3 – and converts it to NH4 + , N mono-oxides (NOx, greenhouse gases), and N2. Denitrification of nitrate produces about 90% N2 and 10% NOx. However, the natural N balance has been affected by industrial N fixation since the green revolution. Symbiotic N amounts to about 100-175 million tons each year in the 1970s world‐ wide, with industrial fixation of 3.5 million tons, and lightning may fix 10 million tons of N, a value that has probably not changed over time [51] . In 1989, industrially fixed N increased to 80 million tons in response to the needs for high-yielding crops [22].

By the year 2050, the world population is expected to double from a level of more than 5 billion. It is reasonable to expect that the need for fixed N for crop production will also at least double. If this is supplied by industrial sources, synthetic fertilizer N use will increase to about 160 million tons of N per year [51]. Consequently because of its relatively low plant uptake level, generally around 50% or less, several major environmental reasons exist to seek alternative fixed N fertilizers, including the fact that it affects the balance of the global N cycle, pollutes groundwater, increases the risk of chemical spills, and increases atmospheric nitrous oxide (N2O), a potent greenhouse gas. The global budget for N2O appears to be out of balance, exceeding sinks by 30-40% and increasing at 0.25% each year [7]. In this case, biological N fixation should receive more attention because about 2 tons of industry-fixed N is needed as fertilizer for crop production to equal the effects of 1 ton of N biologically fixed in a legume crop [51].

In cultivated land, the soil N balance is a complex system covering serial biological processes and physical and chemical processes. It includes plant N uptake, N fixation, organic N mineralization, nitrification and denitrification, nitrate leaching, and other losses, as N2 or NOx, released into the atmosphere [52]. In the case of organic farms, soil available N is primarily from legumes as green manure and organic fertilizers. SOM reportedly supplies most of the N and S and half of the P uptake by plants within an organic farming system [53,54]. The plant tissues of green manure contain most of the micro or macro plant nutrients, including N, potassium (K), P, and S. Phosphates, K, calcium (Ca), magnesium (Mg), S, and other micro plant nutrients are accumulated by cover crops during the growing season. Hoyt indicated the nutrients content of cover crops; see **Table 3** [55]. These nutrients are maintained in the residues of green manure plants; later, they become available to successive crops after incorporation into the soil.

**Table 3.** Green manure biomass productivity and nutrient content (kg ha–1) [55].

During the composting process of green manure, some carbonic and other organic acids are formed as by-products of microbial activities. These organic acids react with insoluble mineral rocks and phosphate precipitates, releasing phosphates and exchangeable nutrients [29]. Gardner and Boundy found that wheat intercropped with white lupin (*Lupin albus L.*) has access to a larger pool of P, Mg, and N than wheat grown in monoculture [30]. The former two nutrients were probably mobilized by exudates of organic acids from the lupin root and then taken up by wheat roots.

The nutrients content of different legumes can be estimated by the mathematical formulation described by Peet [56]:

Rye: N = 0.0194 × biomass – 17.4

**4. Soil N availability and other plant nutrient availability enhancement**

within an agroecosystem.

+

298 Organic Fertilizers - From Basic Concepts to Applied Outcomes

The denitrification process starts with NO3

the soil. Thus, over 90% of soil N is typically NO3

matter decays, NH4

converted into NO3

–

from NO3

crop [51].

Nitrogen plays an important role in yield determination when relatively adequate levels of other agricultural factors exist. Continued use of inorganic fertilizers has not only altered the soil p H, soil structure, and texture, but has also disrupted niches for micro- and mesofauna, which are essential for nutrient recycling [49]. Alternatively, under systems of organic farming management, when industrial N fertilizer is not used, organic matter origin-N, after biological degradation, is converted into mineral N forms, ammonium and nitrate, and becomes a major factor in plant production. However, as the mineral N content in soils increases beyond the capability of plants to take it up, it will cause N leaching and increase other kinds of N losses into the environment. In this case, it is important to understand the N cycle and soil N balance

As common knowledge, the origin of all kinds of N is air N2, 79% by volume of the earth's atmosphere. Soil microorganisms, free-living or associated with legumes, fix atmospheric N. This complex biological process begins with air N and ends with organic N. After organic

– by nitrifying bacteria and generally most NH4

–

greenhouse gases), and N2. Denitrification of nitrate produces about 90% N2 and 10% NOx. However, the natural N balance has been affected by industrial N fixation since the green revolution. Symbiotic N amounts to about 100-175 million tons each year in the 1970s world‐ wide, with industrial fixation of 3.5 million tons, and lightning may fix 10 million tons of N, a value that has probably not changed over time [51] . In 1989, industrially fixed N increased to

By the year 2050, the world population is expected to double from a level of more than 5 billion. It is reasonable to expect that the need for fixed N for crop production will also at least double. If this is supplied by industrial sources, synthetic fertilizer N use will increase to about 160 million tons of N per year [51]. Consequently because of its relatively low plant uptake level, generally around 50% or less, several major environmental reasons exist to seek alternative fixed N fertilizers, including the fact that it affects the balance of the global N cycle, pollutes groundwater, increases the risk of chemical spills, and increases atmospheric nitrous oxide (N2O), a potent greenhouse gas. The global budget for N2O appears to be out of balance, exceeding sinks by 30-40% and increasing at 0.25% each year [7]. In this case, biological N fixation should receive more attention because about 2 tons of industry-fixed N is needed as fertilizer for crop production to equal the effects of 1 ton of N biologically fixed in a legume

In cultivated land, the soil N balance is a complex system covering serial biological processes and physical and chemical processes. It includes plant N uptake, N fixation, organic N mineralization, nitrification and denitrification, nitrate leaching, and other losses, as N2 or

through the process of denitrification in soils [50].

80 million tons in response to the needs for high-yielding crops [22].

, which is ready to be used by higher plants, is released. NH4

, not NH4

and converts it to NH4

+

, although NH4

+

–

+ can be

+ can be formed

– in

+ is modified into NO3

, N mono-oxides (NOx,

Hairy vetch: N = 0.0409 × biomass – 3.1

Crimson clover: N = 0.0204 × biomass + 13.8

Austrian winter pea: N = 0.0402 × biomass – 9.2

Caley peas: N = 0.0426 × biomass – 6.1

Subclover: N = 0.0280 × biomass + 2.9,

where "biomass" is the dry weight in kg ha–1, and the N content, N, is also in Kg acre–1.

For legumes, on average, pounds of K = pounds of N, and pounds of P = 10% of N.

The study of cowpea/maize intercropping shown that cowpea had used atmospheric N for crop growth and also fixed the nutrient into the soil for subsequent crop. The soil residual mineral N was increased by 82% compared with initial soil N. This demonstrated that biological N2 fixation by cowpeas replenished the available N to both crops and also for subsequence crop [57].


# **Sustainable Marketing and Strategy**

Edited byManuel Au-Yong-Oliveira and Maria José Sousa Printed Edition of the Special Issue Published in *Sustainability*

www.mdpi.com/journal/sustainability


**5. Conclusions**

This paper proposes a power transmission system disturbance detection method based on SLCVA*k*NN. The real industrial data collected from the field transformer station are applied to verify the proposed method. By investigating the application results, we can draw the following conclusions.

**Author Contributions:** Conceptualization, S.W. and X.D.; methodology, S.W. and Y.T.; software, Y.T. and X.D.; validation, Y.T. and L.W.; formal analysis, S.W. and Y.T.; investigation, Y.T. and P.S.; resources, L.W. and Q.C.; data curation, Y.T., L.W., and Q.C.; writing—original draft preparation, Y.T. and P.S.; writing—review and editing, S.W. and X.D.; visualization, L.W. and Q.C.; supervision, X.D.; project administration, X.D.; funding acquisition, X.D. All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Shandong Provincial Natural Science Foundation (Grant No. ZR2020MF093), the Major Scientific and Technological Projects of CNPC (Grant No. ZD2019-183- 003), and the Fundamental Research Funds for the Central Universities (that is, the Opening Fund of National Engineering Laboratory of Offshore Geophysical and Exploration Equipment, Grant No. 20CX02310A).

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Conflicts of Interest:** The authors declare no conflict of interest.


*Edited by Natarajan Prabaharan, Marc A. Rosen and Pietro Elia Campana*

This book covers the recent advances in solar photovoltaic materials and their innovative applications. Many problems in material science are explored for enhancing the understanding of solar cells and the development of more efficient, less costly, and more stable cells. This book is crucial and relevant at this juncture and provides a historical overview focusing primarily on the exciting developments in the last decade. This book primarily covers the different Maximum Power Point Tracking control techniques that have led to the improved speed of response of solar photovoltaics, augmented search accuracy, and superior control in the presence of perturbations such as sudden variations in illumination and temperature. Furthermore, the optimal design of a photovoltaic system based on two different approaches such as consumed power and economics is discussed.

ISBN 978-1-78985-403-9

Recent Developments in Photovoltaic Materials and Devices

Published in London, UK © 2019 IntechOpen © Rost-9D / iStock


*Edited by Ana Polona Mivšek*

Midwifery across the globe faces different issues. In some countries the autonomy of the profession is a tradition, while in some societies midwives struggle to practice autonomously the basic competencies. In one part of the world the medicalisation of childbirth is the main issue, preventing the natural processes of pregnancy and childbirth to flow at their own pace, while in other parts of the world midwives struggle with lack of resources to provide safe midwifery care. The authors of this book practice midwifery in different cultures and within different social contexts. They have to deal with different obstacles and seek solutions to diverse problems. With their contributions, they offer an insight into their thinking, their dilemmas, and the problems of midwifery practices in their countries. However, despite different backgrounds, they all have in common a uniform goal—a wish to offer women optimal midwifery care and to improve midwifery services.

ISBN 978-1-78985-533-3

Selected Topics in Midwifery Care

Published in London, UK © 2019 IntechOpen © batock / iStock


Procedure: At first, the students had to group together and deliver the activities as a group. However, as a consequence of COVID-19, teaching was delivered online and the exercises were carried out individually. In this sense, the teacher created an appropriate task so that students would be able to manage all relevant issues under lesson 1. Specifically, a list of activities was given to the students before solving them in a virtual session. Students had to value both the resolution and the result of the activities of their classmates. From the 81 students in the group, 41 of them performed the peer review task voluntarily while

another 40 students did not. Since class attendance was not mandatory and these activities took place during on-site sessions, some students did not get involved in the experience. Others simply did not want to take part in them because of the additional workload. In addition, 133 students from two other academic groups of the same course did not do the peer review task and serves as a control group.

#### 2.4.4. Experience 4

Participants: Students of the "Wireless Networks" course in the "Telematics and Telecommunication Networks" MSc degree.

Procedure: This experience has adopted a model based on the development of projects whose objective is the definition of the wireless elements, technologies and architectures to be applied in order to solve a real-world use case. The general lines of work are proposed (smart cities, smart buildings, security. . . ) where the specific use is defined by the students (e.g., farm security sensors, healthcare monitoring in a hospital. . . ). The project teams were formed by 2–4 students each.

The evaluation of the projects was based on oral presentations of 10 min by each team. These were performed in front of all the students and a jury formed by the teacher and three other invited members with professional experience in wireless networks.

Hence, from the presentation, the projects get two evaluations: one from the jury and one from the rest of the class. Both evaluations were based on the same rubric (see Table 2). The rubric was known in advance for the students, and the evaluation was gathered online after each exposition through a Google Forms based poll.

#### 2.4.5. Experience 5

Participants: Students in the "Renewable Energies" course of the BSc degree "Energy Engineering".

Procedure: Students taking part in this experience were about to address the final year dissertation where they will be evaluated by means of a project report thesis and its defense.

On the first hand, students were grouped in teams of 2–3 members. Each team had to address a project of an installation based on renewable energies. This project had to be real and accurate, and it had to be properly developed and explained. For this purpose, students received previous instructions on how the report should be written. Technical aspects were explained during lessons in class.

Afterwards each team had to expose their project in a 10 min pitch, but because of the pandemic situation, on campus lessons were reduced to the minimum and virtual teaching was the recommendation. Because of that, an alternative activity was designed. This experience consisted in a peer review process where each student had to revise one project among those developed by the others teams. In that manner, every project would be evaluated by two or three students and the teacher. For this purpose a rubric (see Table 3) was designed and provided to each student so they would evaluate the project.

#### 2.4.6. Experience 6

Participants: Students of "Stochastic Models" course in the "Mathematics" BSc degree. Procedure: Following the aforementioned methodology an activity was developed consisting of the realization and presentation, by the students, of a project of analysis and forecast of a time series based on real data. For this purpose, groups of up to three participants were formed. Finally, each student evaluated both the work and the oral presentation of the other projects.

For the implementation of the proposed methodology, an evaluation rubric (see Table 4) was created with ten criteria and several aspects to be taken into account. In the evaluation form, open sections were also considered so that the students could include assessments and proposals for improvement, both of the rubric and of the development of the activity itself.

In order to have a comparison tool to assess whether the activity could be considered valid, the teacher also evaluated the projects and their exhibitions in the same way and under the same rubric used by the students.

#### **3. Results**

As previously detailed, a total of six experiences have been conducted, which are grouped in two categories. On the one hand, Type I experiences (1–3) aim to give new insights into the effectiveness of peer review, that is, how the application of peer review methodology can affect student performance. To that end we have analyzed the the scores of the final exam of the course as previously done by other authors, such as Amendola et al. [12], Conde et al. [18] and Li et al. [31]. In this way, groups with and without peer evaluation during the learning process have been compared.

On the other hand, Type II experiences (4–6) focus on evaluating the reliability of the scores provided by peers by analyzing them in terms of their statistical distribution and their relation to the marks provided by the instructor.

#### *3.1. Experiences Type I*

Results obtained from Type I experiences are displayed in Figures 1 and 2 according to the description given in experiences 1, 2, and 3 in Section 2.4. These diagrams display the number/fraction of students whose score is withing specific ranges. NP (standing for Non-Participant) refers to the fraction of students who did not attend to the final test. The rest of categories are defined following a 10-point scale. Since all the experiments were conducted in the context of the Spanish higher education system, it is considered that 5 is the minimum score to pass the exam. Accordingly, the following intervals [0–5), [5–7), [7–9) and [9–10] correspond to no pass, approved, outstanding and pass with distinction respectively.

Regarding experiences 1 and 2 (Figure 1), students were split into two subgroups: peer review (PR) and the control group (CG). As previously mentioned, the selection bias is based on a self assignment by the students themselves. Members of PR subgroup are those taking part in peer review activities during the learning process. On the other hand, members of CG are not taking any sort of peer review activity. In other words, they have followed a traditional learning process. In addition, the final exam of the course is formed by two tests: test 1 is related to the part of the syllabus where traditional learning process is used, whereas test 2 evaluates competences acquired in the second part of the subject (where only member of PR puts into practice peer review). This means that peer review activities have only been deployed by the members of subgroup PR in test 2 (bold in diagrams).

Based on this grouping, a comparison of the different subgroups based on mean scores and their standard deviation is of interest to check if the students' performance improves as a result of peer review activities. Left-hand side diagrams in Figure 1 describe the distribution of scores based on the number of students within each range, whereas right-hand side diagrams do the same but based on the percentage/fraction of students.

 **test 2 PR**

 test 2 CG

 test 1 CG

 test 1 PR

0

**Figure 1.** *Cont.*

(**d**) Experience 2 (fraction of students).

**Figure 1.** Score distribution obtained in type I experiences 1 and 2.

Relevant conclusions can be drawn after from the results compiled after conducting experience 1 (see Figure 1a,b). Based on the mean scores, the control group (CG) obtained similar grades in both tests (*µ* = 6.01 ± 2.48 for test 1 and *µ* = 6.12 ± 2.46 for test 2). It can be explained since CG members have followed the same traditional learning process for both tests. In contrast, a significant difference has been reported when comparing results between test 1 and test 2 by PR members. Peer review activities allowed an increase in the mean score of test 2 (*µ* = 8.26 ± 1.81) vs. test 1 (*µ* = 6.86 ± 2.37). This shows that peer review has positively contributed to the learning process in the second part of the course being the process of learning from peer's flaws a key asset.

Experience 2 provides analogous results (see Figure 1c,d). One can observe that peer review activities deployed in the second part of the subject (test 2) contributed to an increase in the average score of PR members by 2.41 points (from test 1 *µ* = 6.36 ± 2.37 to test 2 *µ* = 8.77 ± 1.51). It is nevertheless noteworthy that results compiled by CG members have also shown an increase between test 1 and test 2 (*µ* = 6.16 ± 2.24 vs. *µ* = 7.30 ± 2.72) but less significant. This shows that, despite the fact that other factors may affect the average score (some parts of the syllabus may result more complex), the effectiveness of peer review has been proven, as it has shown a consistent improvement in the students performance expressed in terms of their final score.

Regarding experience 3 two figures have been shown (Figure 2a,b). Unlike experiences 1 and 2, only three subgroups have been formed, and a single test has been done covering the whole subject. The first subgroup (PR) is formed by those students who voluntarily decided to take part in the peer review experience (it is displayed in bold in figures). Alternatively, subgroup CG1 is associated to students who did not take part in such activities. It is important to mention that both subgroups (PR and CG1) belong to the same academic group/shift. In addition, subgroup CG2 represents students of the same course but from a different academic group/shift who did not take part in peer review activities (note that due to classroom limitations a course can be divided into different academic groups/shifts). A similar comparison can be set based on the academic results of the three different subgroups. Scores by subgroup PR was 8.52 ± 1.57, which is clearly higher than those obtained by members of CG1 (*µ* = 6.52 ± 2.21) and CG2 (*µ* = 6.80 ± 3.30). In line with experiences 1 and 2, experience 3 also indicates that students taking part in peer review activities benefit noticeably from the experience. All students have gone through the same final evaluation tests and course syllabus.

**Figure 2.** Score distribution obtained in type I experience 3.

#### *3.2. Experiences Type II*

Results concerning type II experiences were assessed by calculating the existing distribution of the score difference [12,30,31] obtained by subtracting the reference-score from the score provided by peers. Here, the reference-score is the one provided by the instructor (experiences 5 and 6) or the average between the score provided by a panel of experts and the instructor (experience 4). A positive difference indicates that the peer's score is higher than the reference-score. In order to unify the criteria, scores will be expressed on a 0–10 scale before calculating the difference.

The items detailed in the rubrics aim to cover most of the competencies playing a relevant role, but they have been grouped into two main categories. The first one refers to items related to the contents (C) of the task carried out by the student group. It basically refers to how students have applied the specific concepts related to the main scope of the course. In contrast, formal aspects (F) refer to whether students have properly applied the available resources and competences to communicate their conclusions and results.

Figure 3 displays the distribution of the score difference grouped in the two aforementioned categories. Left-hand side figures refer to scores related to the contents of the tasks (Figure 3a,c,e). In general terms, scores provided by peers are distributed around the reference-score (i.e., score difference is zero). However, it can be observed that mean

values are slightly positive (from *µ* = 0.71 to *µ* = 0.08 in experiences 4 and 5 respectively) meaning that scores provided by peers are slightly higher than the reference-score (set by the instructor). The adjusted underlying Gaussian probability distribution has also been included just for comparison, where the standard deviation shows that the dispersion of the score difference is around two points (0-10 scale) in the worst scenario.

Right-hand side Figure 3b,d,f show the distribution of the score difference concerning the formal aspects (F category). It shows how dispersed the distribution is of the score difference but considering only interdisciplinary competences (not exclusively related to the topic of the course). Analogous distribution is observed in this case, with standard deviation lower than 2 points in all cases and mean values slightly positive. Only experience 5 (Figure 3) has a relatively higher mean value (*µ* = 1.68 points).

**Figure 3.** Results of Type II experiences according to rubric items category.

In order to answer the question about if peer review is an effective and reliable method for evaluation, the average of all the items of the rubric scores (for both categories) is represented in a single histogram for each experience. As displayed in Figure 4, a global perspective of the distribution is provided, where the mean value of the peer scores is significantly closer to the instructor's reference-grade. Note that in experiences 4 and 6, mean values are relatively low (*µ* = 0.72 and *µ* = 0.11 respectively). Only experience 4 shows a mean value slightly higher (*µ* = 0.96). However, regardless of the experience or classification assumed for the evaluated items, dispersion (standard deviation) is enclosed by 2 points out of 10. These results can be considered as reference values for the level of discrepancy and variability between the teacher and student qualifications in the peer review process.

(**c**) Experience 6 (all items).

**Figure 4.** Results of Type II experiences including all the items in the rubric.

#### **4. Conclusions and Future Work**

When used for educational purposes, peer review methodology is considered a learning technique where students proactively evaluate the work of other students. In this article, an empirical evaluation of peer review has been carried out in a multidisciplinary set of six science and engineering courses in the University of Malaga in Spain, where more than 400 students were involved. In order to answer the two key questions of this study, experiences have been grouped in two different types: (i) those analyzing the impact that peer review methodology has on the students learning process (effectiveness), and (ii) those assessing students' critical sense and the capacity for objectivity in their provided reviews (reliability).

Regarding the effectiveness of the peer review methodology (first key question), it has been possible to validate how the experience has improved the results of those students who have participated. This has been confirmed for different degrees. Here, it can be highlighted that all experiences show a clear improvement in student performance. This is reflected in the general course scores of the participants, being the increase of more than two points (0–10 scale) in the best of cases and at least of one point but always achieving positive results with respect to the control group. Regarding the second key question, we found that the scores provided by the students are very similar to the score assigned by the teacher. Therefore, students are able to evaluate consistently enough according to our results, confirming the feasibility of peer review as a reliable evaluation methodology. Regardless of the type of experience, this methodology has shown to enhance

the learning process prior to evaluation. Not only do students assimilate contents for their first test, but they also develop a well based criteria to identify the mistakes made by other classmates, encouraging their critical sense, and identifying the more complex concepts. This way, students acquire the ability to identify the most common errors allowing them to complement their knowledge of the course more effectively.

After analyzing the application of the peer review methodology, it can be concluded that all the experiences have successfully performed from both academical and motivational perspectives. In this sense, the motivational aspect is key, especially considering remote education conditions. From our point of view, this fact is crucial to encourage students to participate in these initiatives as they clearly improve their academic performance. Hence, peer review can be a key approach for its implementation in the current pandemic scenario where the use of new technologies has become essential in the educational model. Moreover, peer review seems to be an advisable complement to the traditional evaluation process which is frequently considered one of the weak spots of online teaching. In addition, peer review provides the instructor with an invaluable source of information to support a more accurate evaluation.

As future work, a study on how anonymous evaluation affects the results is proposed. It is expected that friendship bias could be mitigated by deploying a series of protocols and procedures to ensure the anonymous nature of the evaluation process. For example, this can be guaranteed by the random allocation of the exercises to be scored following a double-blind review process. This reduces the likelihood that the answers will contain any sort of information about the author of the question. These can be done during the development of the course in question, either in written form or through any computer tool within a classroom setting. In this context, tests might be individual to help the anonymity of the review process.

In addition, based on our experience, we propose a continuous improvement in the rubrics in order to increase the quality and objectivity of the review process. This will be achieved by the redefinition of their format and instructions, the elimination of the points that can be considered weak and the inclusion of new items that can be interesting for the evaluation. These proposals for improvement of rubrics will be gathered from both the analysis of current rubrics as well as the obtained results accompanied with a survey fulfilled by those students that voluntarily participated in the peer review. Moreover, it has been identified that in some cases the correction of exercises requires an excessive amount of time considering the planned students workload. For these, an improvement is deemed necessary to adapt the amount of exercises to be performed during class in order to dedicate more time to the correction to be performed by the students. Another option being envisaged is to dedicate one session to the development of the activities and another to their correction.

Finally, it is planned to study the impact of the peer review methodology in the same six courses in the next years in order to assess its continued use. Moreover, its application to other courses and fields is also planned in order to widen the multidisciplinary nature of the analysis.

**Author Contributions:** This research work has been a collaborative work, but task leaders were assigned in our project plan to organize the workflow. Literature review, S.P.-H., C.M. Conceptualization J.J.S.-A., and A.M.; methodology, P.M.-M., and A.T. (Alicia Tocino); software, J.J.S.-A., and S.F.; validation, S.F., A.T. (Antoni Torres), and R.M.-S.; formal analysis, C.M., and S.P.-H., investigation, C.M., and S.P.-H.; resources, A.T. (Antoni Torres), and P.M.-M.; data curation, A.T. (Antoni Torres), J.J.S.-A.; writing—original draft preparation, A.T. (Antoni Torres), and R.M.-S.; writing—review and editing, S.F.; visualization, R.M.-S., and A.T. (Alicia Tocino); supervision, A.M.; project administration, P.M.-M.; funding acquisition, A.T. (Alicia Tocino). All authors have read and agreed to the published version of the manuscript.

**Funding:** This work was funded by the Spanish Teaching Innovation Project PIE19-209 ("Collaborative evaluation to strengthen student competencies through an active methodology from the teaching and learning process to evaluation") at the University of Malaga.

**Acknowledgments:** The authors are grateful for the helpful and constructive comments of the three reviewers in improving this paper. We would also like to express our gratitude to Pedro Rodríguez Cielos, who guided and helped us as a mentor to conduct this Teaching Innovation Project.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **Abbreviations**

The following abbreviations are used in this manuscript:

#### **References**


**Author details**

Farid A. Badria Liver Research Lab, FAB-Lab, Pharmacognosy Department, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt

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*Research on Natural Phenolic Compounds in FAB-Lab: Nonconventional Industrial… DOI: http://dx.doi.org/10.5772/intechopen.101446*