Set Of Performance Indicators Research Articles

States’ Accountability for Facilitating Parent Involvement under IDEA

Since the reauthorization of the Individuals with Disabilities Education Act (IDEA) in 2004, state IDEA programs have been required to report annually on a set of performance indicators. Indicator 8 of the Part B State Performance Plan is the “percent of parents who report that schools facilitated parent involvement as a means of improving services and results for children with disabilities.” The purpose of this study was to investigate whether changes over time in national and state-level performance on Indicator 8 provide evidence in support of the effectiveness of the accountability requirement related to parent involvement. Data were extracted from states’ Annual Performance Reports and other publicly available documents. Findings indicated that national performance on Indicator 8 increased from 63% in 2006 to 76% in 2018. Within-state change in performance from 2014 to 2019 ranged from –13.47% to +42.50%, with several states indicating dramatic year-to-year changes in their reported performance. The findings raise important questions about the extent to which the indicator in its current form can support the dual purpose of holding states accountable for their facilitation of parents’ involvement and supporting improvement efforts. Implications for both federal policy and state-level action are discussed.

Challenges in surveying tourists’ on-site activity and travel behavior

Given the increasing negative externalities of tourist mobility at the destination, there is a rising demand for reliable data on tourist on-site travel behavior. However, challenges awaiting researchers planning to conduct tourist surveys differ from those known from household surveys. In this paper, we critically review existing traditional and tracking methods, and evaluate their usefulness for surveying tourists. We present a rating system, which, based on a set of performance indicators and weights, returns weighted scores for each method. The proposed system can instruct researchers in choosing the method most adequate to their research question, time frame and budget.

Local productive arrangements and their effects on tourism

This article presents a set of performance indicators to guide the actors to increase their mutual cohesion and facilitate the pursuit of common goals. These indicators were defined based on the authors' expertise in analyzing tourism networks and the results obtained from research in Ouro Preto City, Brazil. In this way, it was possible to perceive the degree of significance of the actors involved in terms of the choice criteria used by visitors to configure their path within the tourist region surveyed and thus strengthen existing relationships.

Education Policy Institutions’ Comprehension of the School as a Learning Organisation Approach: A Case Study of Latvia

The economic crises of recent years, the COVID-19 pandemic and growing dissatisfaction with the quality of education have proved that national education systems throughout the world require large-scale transformations. Effective implementation of these large-scale reforms also requires highly qualified professionals. Latvia has introduced reforms targeting issues in educational philosophy, teaching content, pedagogical approach and school management. The School as a Learning Organisation (SLO) model, which envisages continuous individual and collective learning of all stakeholders involved in the education process, has currently come into the spotlight of policy makers. The SLO consists of seven dimensions: (1) developing and sharing a vision centred on the learning of all students; (2) creating and supporting continuous learning opportunities for all staff; (3) promoting team learning and collaboration among all staff; (4) establishing a culture of inquiry, innovation and exploration; (5) embedding systems for collecting and exchanging knowledge and learning; (6) learning with and from the external environment and larger learning system; and (7) modelling and growing learning leadership. It is characterised by a broad set of performance indicators, the deeper understanding of which requires academic and practical knowledge. The purpose of the current study is to examine the perceptions of representatives of education policy institutions to predict the efficacy of the SLO implementation in Latvia. Three semi-structured focus group discussions were conducted with the participants and deductive and inductive content analyses were carried out. The findings showed that policy makers highlighted “promoting team learning and collaboration among all staff” and “modelling and growing learning leadership” dimensions as the most important and best understood dimensions of the SLO. On the contrary, “embedding systems for collecting and exchanging knowledge and learning” was the least understood dimension by education policy makers. The results of the study indicate that a comprehensive understanding of the SLO model is necessary in order to implement it effectively and for its implementation to promote the transformation of education in Latvia.

Quality assessment of on-campus student housing facilities through a holistic post-occupancy evaluation (A case study of Iran)

ABSTRACT According to studies, students’ living features significantly influence the quality of their education. This paper takes a holistic approach to the post-occupancy evaluation (POE) of on-campus student housing in Iran. The framework was developed following a thorough review of the literature, and the identification of a comprehensive set of performance indicators were categorized into twelve elements and three dimensions technical, functional, and behavioral. Using several complementary techniques resulted in higher qualitative feedback during the evaluation process, leading to more reliable results. The importance-satisfaction matrix was used to determine the quality of improvement priorities. Residents expressed satisfaction with their living environment. They were mainly satisfied with technical and behavioral dimensions; nonetheless, they experienced dissatisfaction with the functional dimension. The study suggests improvements by several facilities such as air conditioning systems, sound insulation, fire detection systems, hygiene, internet speeds and house rules. It also allows for a more comprehensive and realistic prioritization of improvements. This study bridges the research gap and contributes to the need for a more holistic POE framework and several complementary techniques. Furthermore, it extends the limited research on female student housing in Iran by considering a typical and reputable case study. The provided recommendations in this study can act as feedback and feedforward for improving and developing student housing facilities. Abbreviation: POE: post occupancy evaluation; SD: strongly dissatisfied; N: neutral; SS: strongly satisfied; SI: satisfaction index; RII: relative importance index; D: dissatisfied; S: satisfied; MSI: mean satisfaction index

Complex Analysis of an Auxetic Structure under Compressive Loads

Cellular structures subjected to compressive loads provide a reliable solution for improving safety. As a member of cellular material, auxetic metamaterials can enhance performance according to the definition of the negative Poisson ratio. In conjunction with Rapid Prototyping by Additive Manufacturing methods, complex structures can be manufactured using a wide range of materials. This paper debuts the development process of a reliable material model that is useful for the numerical simulation, and further details and investigates the performance indicators of an auxetic structure, namely anti-tetra-chiral. These indicators are related to the force developed during the plateau stage, the length of the plateau stage, and the nominal dimensions of the structure to avoid buckling during compression. Two new indicators discussed in this paper aim to provide a complete set of performance indicators. The first analytical solution provides the displacement of the circular nodes during the compression. The second analytical solution estimates the strain developed in the ligaments. Considering the performance of the processed material, this analysis aims to determine whether the structure can develop the complete plateau stage or whether premature failure will occur.

Exploring An Approach Towards Measuring Student Learning Outcomes: A Case Study For A Pre-Service Teacher Education Programme at A University In Vietnam

Higher education in South-East Asia as elsewhere in the world has been under transformations as it aims to meet increasing demands for quality workforce to fuel the economic growth and global integration. Higher education institutions are striving for quality of student learning and measures have been taken, be they quality assurance initiatives or responsible educational practices, to ultimately demonstrate their accountability towards their educational outputs – the achievement of their student learning outcomes. This paper presents an approach to measuring the attainment of student learning outcomes for a pre-service teacher education programme at a university in Vietnam. It shows attempts being made to an assessment plan to determine whether the intended learning outcomes have been achieved and to what extent. The process involves establishing a set of performance indicators (PIs) which well correspond to the set learning outcomes and identifying various types of direct student achievement data being collected and benchmarked against the set targets The findings allow some generalisations to be drawn on the overall performance of student learning with certain aspects being reported to outperform their counterparts in the programme, especially in the outcomes towards lifelong learning, personal and professional development. The paper also suggests the use of indirect evidence collected via surveys to stakeholders to allow a more comprehensive picture of the performance of student learning from which better-informed decisions could be made on changes in curricular design and delivery.

Evaluating Student Knowledge Assessment Using Machine Learning Techniques

The process of learning about a student’s knowledge and comprehension of a particular subject is referred to as student knowledge assessment. It helps to identify areas where students need additional support or challenge and can be used to evaluate the effectiveness of instruction, make important decisions such as on student placement and curriculum development, and monitor the quality of education. Evaluating student knowledge assessment is essential to measuring student progress, informing instruction, and providing feedback to improve student performance and enhance the overall teaching and learning experience. This research paper is designed to create a machine learning (ML)-based system that assesses student performance and knowledge throughout the course of their studies and pinpoints the key variables that have the most significant effects on that performance and expertise. Additionally, it describes the impact of running models with data that only contains key features on their performance. To classify the students, the paper employs seven different classifiers, including support vector machines (SVM), logistic regression (LR), random forest (RF), decision tree (DT), gradient boosting machine (GBM), Gaussian Naive Bayes (GNB), and multi-layer perceptron (MLP). This paper carries out two experiments to see how best to replicate the automatic classification of student knowledge. In the first experiment, the dataset (Dataset 1) was used in its original state, including all five properties listed in the dataset, to evaluate the performance indicators. In the second experiment, the least correlated variable was removed from the dataset to create a smaller dataset (Dataset 2), and the same set of performance indicators was evaluated. Then, the performance indicators using Dataset 1 and Dataset 2 were compared. The GBM exhibited the highest prediction accuracy of 98%, according to Dataset 1. In terms of prediction error, the GBM also performed well. The accuracy of optimistic forecasts on student performance, denoted as the performance indicator ‘precision’, was highest in GBM at 99%, while DT, RF, and SVM were 98% accurate in their optimistic forecasts for Dataset 1. The second experiment’s findings demonstrated that practically no classifiers showed appreciable improvements in prediction accuracy with a reduced feature set in Dataset 2. It showed that the time required for related learning objects and the knowledge level corresponding to a goal learning object have less impact.

Data availability and participatory approach: the right mix for enhancing Mediterranean fisheries’ sustainability

A misalignment between the legislation and the effectiveness of Mediterranean fisheries management has emerged due to the status of the stocks (still largely in overfishing) and the discontent of stakeholders regarding management plans and tools that are not always recognized as appropriate to the characteristics of the concerned fisheries. Stakeholders’ involvement in management processes is one of the main pillars of the Common Fisheries Policy revision. The literature underlines, in an increasingly urgent manner, the importance of stakeholders fully understanding the contents of management plans and, vice versa, necessary for the successful implementation of policies. Focusing on the path towards sustainability endorsed by the BluFish project, the paper tries to provide an answer about the sustainability of some selected Southern Italian fisheries, by adopting the assessment approach of the Marine Stewardship Council. The assessment approach, based on a set of Performance Indicators and on a well-defined scoring scheme, focuses on three dimensions of sustainability. In addition to the classic assessment of the state of the stocks, there is an extensive screening of the impact of anthropic activity such as fishing on the entire ecosystem, including both the impact on accessory species and on vulnerable habitats and species. The evaluation adopted goes even further, with an approach that also includes the management and governance sphere, also trying to evaluate the level of involvement of the operators in the decision-making process. The paper illustrates that the selected fisheries are not fully sustainable but some of them have excellent potential for improvement even in the short term by identifying and implementing the appropriate action. The most relevant weaknesses identified refer to the low scores obtained for sustainability of stocks, mainly around the Harvest Control Rules (HCR) and the Harvest Strategy indicators, highlighting the importance of improving the management of the assessed stocks. The paper highlights how data and scientific knowledge availability is essential for a detailed mapping and evaluation of fishing activities but also that the path towards more sustainable and responsible fisheries does not work without a strong participation of all the key stakeholders.

Royal family board directors and the level of ESG disclosures in GCC listed firms

PurposeThis study aims to examine the role of royal family members’ board of directors, as a specific aspect of corporate governance, on the firm’s environmental, social and governance (ESG) disclosures. Many firms in the world enjoy special political connections, benefit from tax exemptions and favorable treatments that are largely responsible for their economic endurance and strong performance.Design/methodology/approachThe authors collect data from Thomson Reuters database on Gulf Cooperation Council (GCC)-listed firms for 2010–2018. Royal family board directors’ data is manually collected using a systematic approach to ensure accuracy. Fixed effects’ panel regression model is used to estimate relationships. The authors interact variables to test the moderating effect of board independence and sustainability committee on the influence of royal family board directors.FindingsThis study finds that royal family directors on GCC boards negotiate fewer ESG reporting in firms. While board independence, board gender diversity, sustainability committee and governance committee increase the level of ESG-disclosures in the traditional way of reducing agency costs to stakeholders, this study finds that royal family board members convey beneficial consequences on firms without perceiving the need to disclose their ESG activities. Additionally, these firms do not show a spillover effect from the royal family members on the board’s independence or the existence of a sustainability committee; rather these members use a different channel for protecting and building the business value. These results are robust with respect to controls for company size, leverage, return on assets and growth. Instrumental variables are then introduced in the analysis to perform a sensitivity test.Originality/valueThe study results indicate the need to improve GCC market transparency over supplementary limitations that exist on their corporate governance condition. This may be consequential to regulators, lenders and investors. The results suggest the need to raise awareness of the importance of governance and balancing firms’ financial and social performance in the presence of royal family board directors. Policymakers and governance agencies are responsible for promoting the importance of forming sustainability committees and having a set of performance indicators that measure the effectiveness of their actions.

GNSS Antenna Pattern Prediction and Placement Optimization: A Prototype Method Using Machine Learning to Aid Complex Electromagnetic Simulations Validated on a Vehicle Model

An antenna’s radiation pattern is dependent on its geometrical characteristics and its antenna’s surroundings, materials, and geometries. As such, to predict the antenna’s performance in complex environments, such as that of small antennas on large vehicles, it is necessary to obtain a model that represents such a full scenario, so that the simulation may be accomplished in the process of antenna design and placement. Due to the complex and electrically large nature of some electromagnetic problems, the detailed representation, even for a simplified model, may imply a large computational effort, both in terms of time and memory, is needed to perform the simulation. This paper evaluates how machine learning models can be used to mitigate the computational effort required to predict the behavior of antennas requiring complex modeling. It is proposed to start from a more simplified model of the electromagnetic structure to obtain a prediction for the correct solution, without needing to simulate the full structure in every iteration, and to combine this with prediction algorithms to obtain the solution of the full problem. The proposed solution uses convolutional neural networks (U-Net) of a certain accuracy to help with the correct placement of small antennas on autonomous vehicles. The standard approach requires the simulation of a full model at each test position, requiring high computational time and memory. With this new proposal, it is possible to analyze more positions and radiation patterns in a much shorter time, and with less memory, when compared with the solution from the full model. Along with this methodology for each simulation, a Bayesian optimizer is proposed to improve the search process for the best location, leading to a reduction in the required steps. This methodology was applied to support the correct positioning of a GNSS antenna with reference to a set of performance indicators required for autonomous vehicles, but it can be also applied to larger and more complex structures, allowing one to reduce the simulation time of a large electromagnetic structure and the search time for the optimum location.

Evaluating Environmental and Energy Performance Indicators of Food Systems, within Circular Economy and “Farm to Fork” Frameworks

This study proposes a framework of environmental and energy performance indicators identified and critically evaluated within the scientific literature and the Agricultural European Database for the monitoring and evaluation of the Common Agricultural Policy of the European Union. The identified set of performance indicators encompasses the whole life cycle of agri-food systems from primary production stage until end-of-life stage in agreement with the circular economy and EU “farm to fork strategy” frameworks. In particular, the practices/goals/targets suggested in the latter (e.g., organic farming goals, more relevance assigned to plant-based diets, support for the creation of short supply chains, and reduction in food losses and waste) have guided the search for the main topics of interest in our analysis and the associated environmental and energy indicators. The results of this study evidence a proposed set of performance indicators selected from the literature among LCA and non-LCA indicators (midpoint LCA impacts, cumulative energy use, emergy accounting, and material flow accounting, among others) that could be helpful in integrating the EU CAP indicators for monitoring and evaluating efforts and achieved results toward implementing and controlling the effectiveness of the adopted “farm to fork” policy and related legislative measures, as well as the application of the circular economy model.

Application of Industrial Internet for Equipment Asset Management in Social Digitalization Platform Based on System Engineering Using Fuzzy DEMATEL-TOPSIS

In any industry, Equipment Asset Management (EAM) is at the core of the production activities. With the rapid development of Industrial Internet technologies and platforms, the EAM based on the Industrial Internet has become an important development trend. Meanwhile, the paradigm of EAM is changing, from a single machine to integrated systems, from the phase of using them to the end of their lifecycle, from breakdown maintenance to predictive maintenance, and from local decision-making to collaborative optimization. However, because of the lack of a unified understanding of the Industrial Internet platforms (IIPs) and the lack of a comprehensive reference architecture and detailed implementation framework, the implementation of EAM projects will face greater risks according to special needs in different industries. Based on the method of system engineering, this study proposes a general reference model and a reference architecture of implementation for the Industrial Internet Solution for Industrial Equipment Asset Management (I3EAM). Further, to help enterprise to evaluate and select their best-fit I3EAM scheme and platform partner, we proposed a set of performance indicators of I3EAM schemes and a quantitative decision-making method based on fuzzy DEMATEL-TOPSIS. Finally, a case study for an I3EAM in automated container terminals was conducted. In the multi-criteria decision environment with complex uncertainty, the project group identified the I3EAM metrics priorities and social digitalization platforms that were more in line with the actual needs of the automated container terminal and firms. The complexity and time of the decision-making process were dramatically reduced. In terms of feasibility and validity, the decision result was positively verified by the feedback from the enterprise implementation. The given model, architecture, and method in this study can create a certain reference value for various industrial enterprises to carry out the analysis and top-level planning of their I3EAM needs and choose the partner for co-implementation. In addition, the research results of this study have the potential to support the construction of standard systems and the planning and optimization of the cross-domain social platform, etc.

Managerial Control in an Online Constructivist Learning Environment: A Teacher’s Perspective

This article presents the lessons learned from an online teaching experience in the field of managerial control. The study aims to identify the determinants which influence collaborative behaviors between students in management studies and more specifically during the construction of performance measures. A business simulation specifically elaborated for this study is used. The study is conducted through a particular research design consisting of an online learning environment built on constructivist learning principles. The learning environment simulates the different steps of a performance dashboard creation (a set of performance indicators) for a fictitious organization. The study adopts an exploratory sequential design to explore and examine social behaviors during the process of knowledge construction related to performance measures. It contributes to a better understanding of the role of cognitive and behavioral skills in the profession of management accounting and how teachers can incorporate such aspects into their courses. It helps to build awareness among educators about the benefits of using digital learning solutions to help students in accounting and managerial control develop their professional skills most effectively.

A unified scheme for the benchmarking of upper limb functions in neurological disorders

BackgroundIn neurorehabilitation, we are witnessing a growing awareness of the importance of standardized quantitative assessment of limb functions. Detailed assessments of the sensorimotor deficits following neurological disorders are crucial. So far, this assessment has relied mainly on clinical scales, which showed several drawbacks. Different technologies could provide more objective and repeatable measurements. However, the current literature lacks practical guidelines for this purpose. Nowadays, the integration of available metrics, protocols, and algorithms into one harmonized benchmarking ecosystem for clinical and research practice is necessary.MethodsThis work presents a benchmarking framework for upper limb capacity. The scheme resulted from a multidisciplinary and iterative discussion among several partners with previous experience in benchmarking methodology, robotics, and clinical neurorehabilitation. We merged previous knowledge in benchmarking methodologies for human locomotion and direct clinical and engineering experience in upper limb rehabilitation. The scheme was designed to enable an instrumented evaluation of arm capacity and to assess the effectiveness of rehabilitative interventions with high reproducibility and resolution. It includes four elements: (1) a taxonomy for motor skills and abilities, (2) a list of performance indicators, (3) a list of required sensor modalities, and (4) a set of reproducible experimental protocols.ResultsWe proposed six motor primitives as building blocks of most upper-limb daily-life activities and combined them into a set of functional motor skills. We identified the main aspects to be considered during clinical evaluation, and grouped them into ten motor abilities categories. For each ability, we proposed a set of performance indicators to quantify the proposed ability on a quantitative and high-resolution scale. Finally, we defined the procedures to be followed to perform the benchmarking assessment in a reproducible and reliable way, including the definition of the kinematic models and the target muscles.ConclusionsThis work represents the first unified scheme for the benchmarking of upper limb capacity. To reach a consensus, this scheme should be validated with real experiments across clinical conditions and motor skills. This validation phase is expected to create a shared database of human performance, necessary to have realistic comparisons of treatments and drive the development of new personalized technologies.

Human-centered integrated care pathways for co-creating a digital, user-centric health information solution

PurposeA broader challenge of co-creating digital solutions with patients addresses the question how to apply an open-access digital platform with trusted digital health information as a measure to transform the way patients access and understand health information. It further addresses use this for adherence to treatment, risk minimization and quality of life throughout the integrated patient journey. The aim of this paper is to demonstrate the early steps in towards progress to co-creating the digital solution.Design/methodology/approachTo coordinate the co-creation process, the authors established a multiphased plan to deep-dive into user needs and behaviors across patient journeys, to identify nuances and highlight important patterns in stakeholder and end-user segment at various stages in the patient's journey.FindingsA set of tools was designed to serve as a human-centered compass throughout the lifecycle of the project. Those tools include shared objects; personas, user journeys, a set of performance indicators with related requirements – all those tools being consistently refined in ongoing co-creation workshops with members of the cross-functional stakeholder groups.Originality/valueIn this study, a multidisciplinary, public-private partnership looked at integrated digital tool to improve access, understanding and adherence to treatment for diverse groups of patients across all stages of their health journeys in a number of countries including European Union (EU) and United States of America (USA). As a result of this work, the authors attempt to increase the possibility that the improved availability and understanding of health information from trusted sources translates to higher levels of adherence to treatment, safer use of medication (pharmacovigilance), better health outcomes and quality of life integrated in the patient's journey.

Information fusion on delivery: A survey on the roles of mobile edge caching systems

Edge caching, which offers application versatility and a range of benefits, has exerted a significant impact on the adoption and development of fifth-generation networks and applications. While many extensive studies on edge caching have been proposed to improve certain system features, a thorough tutorial providing insight into the role of edge caching on mobile data traffic processing is still required. Motivated by these concerns, this study was designed to offer an exhaustive assessment of mobile edge caching. To clarify the role of mobile edge caching techniques, a systematic overview of the state-of-the-art caching models and operations is provided. Subsequently, a complete set of performance indicators is extensively investigated, including hit ratio, storage efficiency, energy efficiency, spectrum efficiency, service availability, and latency, to comprehensively examine each of the caching policy goals. Furthermore, an inquiry into the aforementioned metrics is conducted using popular technological methodologies, such as machine learning, game theory, and optimization techniques. In addition, common use cases and applications for the observation and assessment of caching methods in practice, are described. Finally, the remaining research challenges and future directions of edge caching are discussed.

Research on sustainability leadership in higher education: a scoping review

PurposeDespite the centrality of leadership to the successful transformation of universities toward sustainability, the literature on the role and practices of sustainability leadership in higher education remains poorly developed. To address this gap, this study aims to develop a conceptual model of sustainability leadership in higher education.Design/methodology/approachThe study adopts the scoping review method to review, critique and synthesize relevant literature.FindingsThe resulting model of sustainability leadership in higher education proposes that sustainability leadership in higher education has the potential to transform university practices through reorientation and stewardship of the institutional mission and strengthening the commitment of stakeholders. Sustainability leadership has the potential to create a positive effect on a balanced set of performance indicators, as well as contributing to institutional and societal resilience in the longer term.Originality/valueSustainability leadership in higher education should be given prominence in its own right due to the unique organizational context of universities. This study synthesized the current discourse on sustainability leadership in higher education and its distinct attributes toward sustainable development.

Developing key performance indicators for the Canadian chiropractic profession: a modified Delphi study

BackgroundThe purpose of this study is to develop a list of performance indicators to assess the status of the chiropractic profession in Canada.MethodWe conducted a 4-round modified Delphi technique (March 2018–January 2020) to reach consensus among experts and stakeholders on key status indicators for the chiropractic profession using online questionnaires. During the first round, experts suggested indicators for preidentified themes. Through the following two rounds, the importance and feasibility of each indicator was rated on an 11-point Likert scale, and their related potential sources of data identified. In the final round, provincial stakeholders were recruited to rate the importance of the indicators within the 90th percentile and identified those most important to their organisation.ResultsThe first round generated 307 preliminary indicators of which 42 were selected for the remaining rounds, and eleven were preferentially selected by most of the provincial stakeholders. Experts agreed the feasibility of all indicators was high, and that data could be collected through a combination of data obtained from professional liability insurance records and survey(s) of the general population, patients, and chiropractors.ConclusionsA set of performance indicators to assess the status of the Canadian chiropractic profession emerged from a scientific and stakeholder consensus.

Evaluation of Spatiotemporal Patterns of the Spinal Muscle Coordination Output during Walking in the Exoskeleton.

Recent advances in the performance and evaluation of walking in exoskeletons use various assessments based on kinematic/kinetic measurements. While such variables provide general characteristics of gait performance, only limited conclusions can be made about the neural control strategies. Moreover, some kinematic or kinetic parameters are a consequence of the control implemented on the exoskeleton. Therefore, standard indicators based on kinematic variables have limitations and need to be complemented by performance measures of muscle coordination and control strategy. Knowledge about what happens at the spinal cord output level might also be critical for rehabilitation since an abnormal spatiotemporal integration of activity in specific spinal segments may result in a risk for abnormalities in gait recovery. Here we present the PEPATO software, which is a benchmarking solution to assess changes in the spinal locomotor output during walking in the exoskeleton with respect to reference data on normal walking. In particular, functional and structural changes at the spinal cord level can be mapped into muscle synergies and spinal maps of motoneuron activity. A user-friendly software interface guides the user through several data processing steps leading to a set of performance indicators as output. We present an example of the usage of this software for evaluating walking in an unloading exoskeleton that allows a person to step in simulated reduced (the Moon’s) gravity. By analyzing the EMG activity from lower limb muscles, the algorithms detected several performance indicators demonstrating differential adaptation (shifts in the center of activity, prolonged activation) of specific muscle activation modules and spinal motor pools and increased coactivation of lumbar and sacral segments. The software is integrated at EUROBENCH facilities to benchmark the performance of walking in the exoskeleton from the point of view of changes in the spinal locomotor output.