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The study of educational innovations has attracted increasing attention from academics and researchers around the world. Educational innovation proposes the implementation of new approaches or practices that are beneficial and make an impact on individuals or academic communities. The current educational model of many higher education institutions (HEIs) was not designed for this generation of “digital natives”. For this reason, HEIs face the challenge of building teaching strategies that generate meaningful educational experiences. This research seeks to address this issue through a systematic mapping that includes empirical research papers from 2015 to 2020 that study innovations in educational practices using mobile devices. A qualitative and quantitative approach was applied using a four-stage research methodology to evidence innovation in higher education. After employing the selected methodology and applying all the exclusion criteria, 27 papers related to the research topic were identified. Mapping was also performed between the corpus of papers and five dimensions on educational innovation (the purpose of learning, the context of learning, the role of the teacher, the role of the learner, and the evidence of the outcome). The findings reveal that the role of the teacher is the dimension that is least analyzed in innovation initiatives, whereas the most analyzed dimension is the purpose of learning. The goal of this work was to explore and identify educational innovations and unveil uncovered fields of research to generate opportunities for new lines of research in educational innovation.

Organizations around the world require a sound process of change management to innovate and remain competitive over time. Change and knowledge management needs to be supported with the right tools to overcome the challenges of transformations and transitions in the business models and processes of diverse organizations. Steering boards can use enterprise architecture (EA) to implement new knowledge management initiatives in their strategic planning. EA allows companies to model the current situation (as-is models) of the organization and the desired future scenarios (to-be models) and to establish road maps to enable adequate transformations. Different frameworks exist in the market that support the management of organizations, for example: Control Objectives for Information and Related Technologies (COBIT), Information Technology Infrastructure Library (ITIL), quality models such as the one proposed by the European Foundation for Quality Management (EFQM) and systems such as the Balanced Scorecard (BSC) are widely used for the management of business and information technologies (IT).  However, EA is not widely used with the other mentioned tools. This paper analyzes EA as a tool for change and knowledge management and compares its functionality with other frameworks in the market. The analysis performed in this paper checks if EA can be used and is compatible with other frameworks. To answer this question, an analysis of the most important processes, good practices, perspectives and tools provided by each framework was performed., Las organizaciones de todo el mundo requieren un proceso sólido de gestión del cambio para innovar y seguir siendo competitivas a lo largo del tiempo. La gestión del cambio y del conocimiento debe ser respaldada con las herramientas adecuadas para superar los desafíos de las transformaciones y transiciones en los modelos y procesos de negocios de diversas organizaciones. Las juntas directivas pueden utilizar la arquitectura empresarial (AE) para implementar nuevas iniciativas de gestión del conocimiento en su planificación estratégica. AE permite a las empresas modelar la situación actual de la organización y los escenarios futuros deseados y establecer mapas de ruta para permitir las transformaciones adecuadas. Existen diferentes marcos de trabajo que apoyan la gestión, por ejemplo: Objetivos de control para información y tecnologías relacionadas (COBIT, por su sigla en inglés), Biblioteca de infraestructura de tecnología de la información (ITIL, por su sigla en inglés), modelos de calidad como el de la Fundación Europea para la Gestión de la Calidad (EFQM, por su sigla en inglés) y sistemas como el Cuadro de mando Integral (BSC, por su sigla en inglés). Sin embargo, la AE no es muy utilizada junto con las herramientas mencionadas. Este documento analiza AE como una herramienta para el cambio y la gestión del conocimiento y compara su funcionalidad con otros marcos en el mercado. El análisis realizado en este documento comprueba si se puede utilizar AE y es compatible con otros marcos de trabajo para gestionar el cambio organizativo y la gestión del conocimiento.

Los sistemas de registro y de reporte de datos son de gran interés, puesto que respaldan la reproducibilidad y transparencia científica. La investigación actual genera una gran cantidad de datos que ya no se pueden documentar utilizando cuadernos de laboratorio de papel (CLP). Los cuadernos electrónicos de laboratorio (CEL) podrían ser una solu-ción prometedora para reemplazar los CLP y promover la reproducibilidad científica y su transparencia. Anteriormente analizamos cinco CEL y realizamos dos encuestas para implementar un CEL en un instituto de investigación biomédica. Entre los CEL proba-dos, encontramos que Microsoft OneNote presenta numerosas características relacio-nadas con las mejores funcionalidades del CEL. Además, ambos grupos encuestados prefirieron OneNote sobre un CEL científico (Elements de PerkinElmer). Sin embargo, OneNote es una aplicación general para tomar notas que no ha sido diseñada para fi-nes científicos. Por lo tanto, en este trabajo proporcionamos varias pautas para adaptar OneNote a un flujo de trabajo experimental.

The large volumes of data (Big Data) that are generated on a global scale and within organizations along with the knowledge that resides in people and in business processes makes organizational knowledge management (KM) very complex. A right KM can be a source of opportunities and competitive advantage for organizations that use their data intelligently and subsequently generate knowledge with them. Two of the fields that support KM and that have had accelerated growth in recent years are business intelligence (BI) and enterprise architecture (EA). On the one hand, BI allows taking advantage of the information stored in data warehouses using different operations such as slice, dice, roll-up, and drill-down. This information is obtained from the operational databases through an extraction, transformation, and loading (ETL) process. On the other hand, EA allows institutions to establish methods that support the creation, sharing and transfer of knowledge that resides in people and processes through the use of blueprints and models. One of the objectives of KM is to create a culture where tacit knowledge (knowledge that resides in a person) stays in an organization when qualified and expert personnel leave the institution or when changes are required in the organizational structure, in computer applications or in the technological infrastructure. In higher education institutions (HEIs) not having an adequate KM approach to handle data is even a greater problem due to the nature of this industry. Generally, HEIs have very little interdependence between departments and faculties. In other words, there is low standardization, redundancy of information, and constant duplicity of applications and functionalities in the different departments which causes inefficient organizations. That is why the research performed within this dissertation has focused on finding an adequate KM method and researching on the right technological infrastructure that supports the management of in

Nowadays, researchers analyse student data to predict the graduation rate by looking at the characteristics of students enrolled and to take corrective actions at an early stage or improve the admission process. Educational data mining (EDM) is an emerging field that can support the implementation of changes in the management of higher education institutions. EDM analyses educational data using the development and the application of data mining (DM) methods and algorithms to information stored in academic data repositories. The purpose of this paper is to review which methods and algorithms of DM can be used in the analysis of educational data to improve decision-making. Furthermore, it evaluates these algorithms using a dataset composed of student data in the computer science school of a private university. The core of the analysis is to discover trends and patterns of study in the graduation rate indicator. Finally, it compares these methods and algorithms and suggests which has the best precision in certain scenarios. Our analyses suggest that random trees had better precision but had limitations due to the difficulty of interpretation while the J48 algorithm had better possibilities of interpretation of results in the visualisation of the classification of data and only had slightly inferior performance.

Advances in science and technology, the Internet of Things, and the proliferation of mobile apps are critical factors to the current increase in the amount, structure, and size of information that organizations have to store, process, and analyze. Traditional data storages present technical deficiencies when handling huge volumes of data and are not adequate for process modeling and business intelligence; to cope with these deficiencies, new methods and technologies have been developed under the umbrella of big data. However, there is still the need in higher education institutions (HEIs) of a technological tool that can be used for big data processing and knowledge management (KM). To overcome this issue, it is essential to develop an information infrastructure that allows the capturing of knowledge and facilitates experimentation by having cleaned and consistent data. Thus, this paper presents a hybrid information infrastructure for business intelligence and analytics (BI&A) and KM based on an educational data warehouse (EDW) and an enterprise architecture (EA) repository that allows the digitization of knowledge and empowers the visualization and the analysis of dissimilar organizational components as people, processes, and technology. The proposed infrastructure was created based on research and will serve to run different experiments to analyze educational data and academic processes and for the creation of explicit knowledge using different algorithms and methods of educational data mining, learning analytics, online analytical processing (OLAP), and EA analytics.

Organizations around the world require a sound process of change management to innovate and remain competitive over time. Change and knowledge management needs to be supported with the right tools to overcome the challenges of transformations and transitions in the business models and processes of diverse organizations. Steering boards can use enterprise architecture (EA) to implement new knowledge management initiatives in their strategic planning. EA allows companies to model the current situation (as-is models) of the organization and the desired future scenarios (to-be models) and to establish road maps to enable adequate transformations. Different frameworks exist in the market that support the management of organizations, for example: Control Objectives for Information and Related Technologies (COBIT), Information Technology Infrastructure Library (ITIL), quality models such as the one proposed by the European Foundation for Quality Management (EFQM) and systems such as the Balanced Scorecard (BSC) are widely used for the management of business and information technologies (IT). However, EA is not widely used with the other mentioned tools. This paper analyzes EA as a tool for change and knowledge management and compares its functionality with other frameworks in the market. The analysis performed in this paper checks if EA can be used and is compatible with other frameworks. To answer this question, an analysis of the most important processes, good practices, perspectives and tools provided by each framework was performed., Las organizaciones de todo el mundo requieren un proceso sólido de gestión del cambio para innovar y seguir siendo competitivas a lo largo del tiempo. La gestión del cambio y del conocimiento debe ser respaldada con las herramientas adecuadas para superar los desafíos de las transformaciones y transiciones en los modelos y procesos de negocios de diversas organizaciones. Las juntas directivas pueden utilizar la arquitectura empresarial (AE) para implementar nuevas iniciativas de gestión del conocimiento en su planificación estratégica. AE permite a las empresas modelar la situación actual de la organización y los escenarios futuros deseados y establecer mapas de ruta para permitir las transformaciones adecuadas. Existen diferentes marcos de trabajo que apoyan la gestión, por ejemplo: Objetivos de control para información y tecnologías relacionadas (COBIT, por su sigla en inglés), Biblioteca de infraestructura de tecnología de la información (ITIL, por su sigla en inglés), modelos de calidad como el de la Fundación Europea para la Gestión de la Calidad (EFQM, por su sigla en inglés) y sistemas como el Cuadro de mando Integral (BSC, por su sigla en inglés). Sin embargo, la AE no es muy utilizada junto con las herramientas mencionadas. Este documento analiza AE como una herramienta para el cambio y la gestión del conocimiento y compara su funcionalidad con otros marcos en el mercado. El análisis realizado en este documento comprueba si se puede utilizar AE y es compatible con otros marcos de trabajo para gestionar el cambio organizativo y la gestión del conocimiento.

Los sistemas de registro y de reporte de datos son de gran interés, puesto que respaldan la reproducibilidad y transparencia científica. La investigación actual genera una gran cantidad de datos que ya no se pueden documentar utilizando cuadernos de laboratorio de papel (CLP). Los cuadernos electrónicos de laboratorio (CEL) podrían ser una solu-ción prometedora para reemplazar los CLP y promover la reproducibilidad científica y su transparencia. Anteriormente analizamos cinco CEL y realizamos dos encuestas para implementar un CEL en un instituto de investigación biomédica. Entre los CEL proba-dos, encontramos que Microsoft OneNote presenta numerosas características relacio-nadas con las mejores funcionalidades del CEL. Además, ambos grupos encuestados prefirieron OneNote sobre un CEL científico (Elements de PerkinElmer). Sin embargo, OneNote es una aplicación general para tomar notas que no ha sido diseñada para fi-nes científicos. Por lo tanto, en este trabajo proporcionamos varias pautas para adaptar OneNote a un flujo de trabajo experimental.

[Abstract] Scientific data recording and reporting systems are of a great interest for endorsing reproducibility and transparency practices among the scientific community. Current research generates large datasets that can no longer be documented using paper lab notebooks (PLNs). In this regard, electronic laboratory notebooks (ELNs) could be a promising solution to replace PLNs and promote scientific reproducibility and transparency. We previously analyzed five ELNs and performed two survey-based studies to implement an ELN in a biomedical research institute. Among the ELNs tested, we found that Microsoft OneNote presents numerous features related to ELN best functionalities. In addition, both surveyed groups preferred OneNote over a scientifically designed ELN (PerkinElmer Elements). However, OneNote remains a general note-taking application and has not been designed for scientific purposes. We therefore provide a quick guide to adapt OneNote to an ELN workflow that can also be adjusted to other nonscientific ELNs.

Cloud computing services are nowadays advertised as an emerging business model. Moreover, these services bring innovative solutions in a more sophisticated competitive market. But, the decision for their adoption could be significantly reduced due to organizations’ concerns related to security, privacy, and trust. The challenge involves such questions as where to start, which provider should the company choose or whether it is even worthwhile. Thus, this paper proposes an improved unified framework, based on a previous study where a 6 step process framework was introduced. This improved framework add one new step for security and control after the migration process. At the end, a 7 processes framework is proposed aimed to fulfill organizations’ concerns when decide to adopt cloud computing services with a follow-up step. This additional step intends to help IT directors to make sure everything is working properly in a methodological way, in order to achieve a successful cloud computing migration process. An effective solution that is gaining momentum and popularity for competitive organizations.&nbsp, Los servicios de computación en la nube hoy en día se promocionancomo un modelo de negociosemergente. Además, estos servicios brindan soluciones innovadoras en un mercado competitivo más sofisticado. Sin embargo, la decisión de su adopción podría reducirse significativamente debido a las preocupaciones de las organizaciones relacionadas con la seguridad, la privacidad y la confianza. El desafío involucra preguntas tales como dónde comenzar, qué proveedor debe elegir la compañía o si vale la pena. Por lo tanto, este documento propone un marco de trabajo unificado y mejorado, basado en un estudio previo donde se introdujo ya un proceso de 6 pasos. Este marco de trabajo mejorado añadeun nuevo paso para el control y la seguridad después del proceso de migración. En sí, se propone un marco de trabajo de 7 procesos dirigido a satisfacer las preocupaciones de las organizaciones cuando deciden adoptar servicios de computación en la nube incluidoelprocesode seguimiento. Este paso adicional tiene la intención de ayudar a los directores de TI a asegurarse que todo funcionecorrectamente de forma metodológica, a fin de lograr un proceso exitoso de migración de la infraestructura de TI ala nube. Una solución efectiva que está ganando popularidade impulsodentro delas organizaciones competitivas.

Data warehousing (DW) is a widespread and essential practice in business organizations that support the data analytic and decision-making process. Despite the importance of DW in complex organizations, the adoption of a data warehouse (DWH) in education is apparently lower compared with other industries. To clarify this situation, this paper presents a systematic mapping that includes the study of empirical research papers from 2008 to 2018 on the topic of DW in education. For this paper, we applied a qualitative and quantitative approach based on a four-stage research method with the objective to have a holistic view of DWHs in education. After filtering and applying the proposed method, 34 relevant papers were identified and studied in detail. The study revealed interesting facts; for example, Kimball’s approach is the most applied methodology for DWH design in education. In addition, a mapping between this comprehensive collection of research papers covering educational DW and six dimensions of analysis (schema proposal, analysis of the user requirements, analysis of the business requirements, effectiveness, implementation, and data analysis) was performed. From this analysis, we discovered that the star schema is the most implemented approach. The purpose of the mapping was to explore and identify the priority areas of research and the research gaps within the academic community. These gaps are a source of opportunities to start new lines of research.

Knowledge Management (KM) is a practice that allows the creation, use, distribution and transfer of knowledge in organizations. Different KM frameworks exist that include business intelligence or enterprise architecture (EA) components for the implementation of KM in organizations. EA tools are used to digitize, relate and visualize the following dimensions of knowledge: organizational structure, business processes, applications and technology. The objective of this paper is to assess the role of EA as a key component in KM and to suggest software evaluation methodologies that can be adapted for the field of EA. For this, an investigation was realized to identify the existing software evaluation methodologies in the market and to filter those that can be adapted for the field of EA. The methodology used for the research was qualitative and exploratory using a case study performed in an international logistic service provider. The case study describes the process done for the selection of the evaluation methodology. Furthermore, it describes the steps for knowledge digitization., La gestión del conocimiento (GC) es una práctica de administración que permite la creación, uso, distribución y transferencia del conocimiento en organizaciones. Existen marcos de referencia de GC que incluyen componentes de inteligencia de negocios o de arquitectura empresarial (AE) para la implementación de proyectos de GC en organizaciones. Las herramientas de AE son usadas para digitalizar, relacionar y visualizar varias dimensiones de conocimiento como son: estructura organizacional, procesos de negocio, aplicaciones e infraestructura tecnológica. Este artículo tiene como objetivo evaluar el rol de la AE como componente clave de la GC y sugerir metodologías que pueden ser usadas para evaluar herramientas de software de AE. Para esto se realizó una revisión bibliográfica de las metodologías de evaluación de software existente en el mercado y se eligieron aquellas que pueden ser adaptadas para el campo de la AE. Está investigación fue cualitativa y exploratoria a través de un caso de estudio desarrollado en un proveedor de servicios logísticos con presencia internacional. El caso de estudio muestra el proceso realizado para elegir la metodología de evaluación. Además, se describen los pasos para la digitalización del conocimiento organizacional.

La gestión del conocimiento (GC) es una práctica de administración que permite la creación, uso, distribución y transferencia del conocimiento en organizaciones. Existen marcos de referencia de GC que incluyen componentes de inteligencia de negocios o de arquitectura empresarial (AE) para la implementación de proyectos de GC en organizaciones. Las herramientas de AE son usadas para digitalizar, relacionar y visualizar varias dimensiones de conocimiento como son: estructura organizacional, procesos de negocio, aplicaciones e infraestructura tecnológica. Este artículo tiene como objetivo evaluar el rol de la AE como componente clave de la GC y sugerir metodologías que pueden ser usadas para evaluar herramientas de software de AE. Para esto se realizó una revisión bibliográfica de las metodologías de evaluación de software existente en el mercado y se eligieron aquellas que pueden ser adaptadas para el campo de la AE. Está investigación fue cualitativa y exploratoria a través de un caso de estudio desarrollado en un proveedor de servicios logísticos con presencia internacional. El caso de estudio muestra el proceso realizado para elegir la metodología de evaluación. Además, se describen los pasos para la digitalización del conocimiento organizacional., Knowledge Management (KM) is a practice that allows the creation, use, distribution and transfer of knowledge in organizations. Different KM frameworks exist that include business intelligence or enterprise architecture (EA) components for the implementation of KM in organizations. EA tools are used to digitize, relate and visualize the following dimensions of knowledge: organizational structure, business processes, applications and technology. The objective of this paper is to assess the role of EA as a key component in KM and to suggest software evaluation methodologies that can be adapted for the field of EA. For this, an investigation was realized to identify the existing software evaluation methodologies in the market and to filter those that can be adapted for the field of EA. The methodology used for the research was qualitative and exploratory using a case study performed in an international logistic service provider. The case study describes the process done for the selection of the evaluation methodology. Furthermore, it describes the steps for knowledge digitization.

This paper brings to light data security issues and concerns for organizations by moving their Enterprise Resource Planning (ERP) systems to the cloud. Cloud computing has become the new trend of how organizations conduct business and has enabled them to innovate and compete in a dynamic environment through new and innovative business models. The growing popularity and success of the cloud has led to the emergence of cloud-based Software-as-a-Service (SaaS) ERP systems, a new alternative approach to traditional on-premise ERP systems. Cloud-based ERP has a myriad of benefits for organizations. However, infrastructure engineers need to address data security issues before moving their enterprise applications to the cloud. Cloud-based ERP raises specific concerns about the confidentiality and integrity of the data stored in the cloud. Such concerns that affect the adoption of cloud-based ERP are based on the size of the organization. Small to medium enterprises (SMEs) gain the maximum benefits from cloud-based ERP as many of the concerns around data security are not relevant to them. On the contrary, larger organizations are more cautious in moving their mission critical enterprise applications to the cloud. A hybrid solution where organizations can choose to keep their sensitive applications on-premise while leveraging the benefits of the cloud is proposed in this paper as an effective solution that is gaining momentum and popularity for large organizations.

(Received: 2014/02/14 - Accepted: 2014/03/25)Enterprise Architecture (EA) has emerged as one of the most important topics to consider in Information System studies and has grown to become an essential business management activity to visualize and evaluate the future direction of a company. Nowadays in the market there are several software tools that support Enterprise Architects to work with EA. In order to decrease the risk of purchasing software tools that do not fulfill stakeholder´s needs is important to assess the software before making an investment. In this paper a literature review of the state of the art of EA will be done. Furthermore evaluation initiatives and existing information systems are analyzed which can support decision makers in the appropriate software tools for their companies., (Recibido: 2014/02/14 - Aceptado: 2014/03/25)La Arquitectura Empresarial (AE) ha emergido como uno de los temas más importantes a considerar en estudios de Sistemas de Información y ha evolucionado hasta convertirse en una actividad de gestión de negocios para visualizar y evaluar la dirección futura de una compañía. Hoy en día existen en el mercado diversas herramientas de software que apoyan a los Arquitectos Empresariales para trabajar con AE. Con el propósito de disminuir el riesgo de comprar herramientas de software que no satisfacen las necesidades de sus directores es importante evaluar el software antes de realizar la inversión. En este documento se realizará una revisión de literatura del estado de arte de AE. Además se analizan iniciativas de evaluación y sistemas de información que pueden dar dirección a las personas con poder de decisión para elegir las herramientas de software apropiadas para sus compañías.

(Received: 2014/11/26 - Accepted: 2014/12/17)Enterprise Architecture (EA) is conceived nowadays as an essential management activity to visualize and evaluate the future direction of a company. The objective of this paper is to make a literature review on EA to evaluate its role as management tool. It is also explained how EA can fulfill two fundamental purposes, first as a tool for assessing the current situation (self-assessment) of an organization; second as a tool to model and simulate future scenarios that allow better decision making for the restructuration and development of improvement plans. Furthermore an analysis is made of the integration possibilities of EA with other business management methodologies, as balanced score card (BSC) and the model of the European Foundation for Quality Management (EFQM). As the result a management framework is presented, which includes the required elements to achieve excellence and quality standards in organizations., (Recibido: 2014/11/26 - Aceptado: 2014/12/17)La Arquitectura Empresarial (AE) se concibe hoy en día, como una actividad esencial de gestión para visualizar y evaluar la dirección futura de una organización u compañía. Este documento tiene como objetivo realizar una revisión de literatura de AE para evaluar su rol como herramienta de gestión. Se detallará también como la AE cumple dos propósitos fundamentales, primero como herramienta de diagnóstico institucional y autoevaluación para los procesos del negocio, aplicaciones e infraestructura tecnológica; segundo como herramienta para simular escenarios futuros que permita optimizar la toma de decisiones para la reestructuración y creación de planes de mejora. Además se analizan posibilidades para integrar AE con otras metodologías de gestión de negocios como el Cuadro de Mando Integral (Balanced Score Card) y el modelo europeo de calidad EFQM. Como resultado se presenta un marco de gestión de negocios con los elementos que se requieren para alcanzar estándares de excelencia y calidad en las organizaciones.

(Received: 2013/09/30 - Accepted: 2013/12/02)Inventory Management in Spare Parts Supply Chains (IMSPSC) plays an important role for both the Customer Company who wants to remain operational despite flaws in its machinery or equipment and the Supplier Company or Producer that want to improve their post sales service processes. The increasing importance of IMSPSC for the performance of companies calls for improved and innovative strategies in this area. This paper describes Single Echelon Inventory Strategies in Spare Parts management practices and serves as a source for deciding on the best strategy depending on the type of business and application. Nowadays these practices are not only a legal obligation of an organization but an opportunity to increase profits and to build long term commercial relationships and loyalty with customers., (Recibido: 2013/09/30 - Aceptado: 2013/12/02)La Gestión de Inventarios en Cadenas de Suministro de Repuestos (GICSR) juega un rol importante tanto para la Compañía Cliente que desea mantenerse operativa a pesar de fallas en la maquinaria o equipos y la Compañía Proveedora o Productora que desea mejorar sus procesos de servicios de post venta. El incremento en la importancia de GICSR requiere la búsqueda de la mejora e innovación de las estrategias en esta área. Este artículo describe estrategias de Nivel Simple de gestión de inventarios en prácticas de administración de repuestos y sirve como una fuente para decidir sobre la mejor estrategia en función del tipo de negocio y la aplicación. Hoy en día estas prácticas no son solo una obligación legal de una organización sino también una oportunidad de construir lealtad y relaciones comerciales a largo plazo con los clientes.