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El objetivo del estudio es revelar en qué medida los universitarios leen las encuestas de evaluación del profesorado cuando se aplican incentivos por participación. Se desarrolla un estudio de carácter cuantitativo, en el que, se adopta una metodología de tipo experimental con dos grupos. El primero realiza la valoración de su docente en un escenario libre de incentivos, el segundo completa la encuesta en un escenario de participación incentivada. El estudio considera además dos tipologías de cuestionario: por un lado, escalas de Likert y, por otro, escalas con episodios de comportamiento BARS. La investigación emplea análisis descriptivos, pruebas t-Student y análisis de correlaciones de Pearson. Los resultados revelan diferencias en el tiempo invertido cuando la participación es incentivada. Se concluye que los instrumentos con escalas de Likert no parecen favorecer una óptima lectura y cumplimentación de la encuesta cuando la evaluación introduce recompensas. Esta situación puede ser mejorada empleando cuestionarios BARS. El presente estudio arroja luz sobre un problema prácticamente ignorado por investigaciones previas, sino que, además, aborda el mismo proponiendo alternativas de mejora.

El presente trabajo examina los aspectos a considerar para alcanzar estrategias de marketing en redes sociales más eficientes. Los autores revelan las variables que llevan al usuario a reconocer, empleando retuits y favoritos, las publicaciones realizadas por las cuentas corporativas de instituciones universitarias. La investigación explora una muestra de diez universidades españolas y un total de 18.092 publicaciones, en la red social Twitter. El estudio adopta una metodología cuantitativa en la que se examinan treinta variables. Los investigadores llevan a cabo un análisis descriptivo y dos regresiones lineales; revelando: (a) las tendencias de uso habituales, y (b) las variables que inciden en el reconocimiento del contenido publicado a través de retuits, por un lado, y de favoritos, por otro. Los resultados corroboran la existencia de dos modelos de regresión robustos. El primero (p-valor < ,0001 y R2= ,792) muestra cómo el reconocimiento de las publicaciones mediante retuits viene determinado por el uso de enlaces y hashtags. El segundo (p-valor < ,0001 y R2= ,886), por su parte, revela que el reconocimiento del contenido en forma de favoritos está condicionado por el volumen de publicaciones diarias y las publicaciones realizadas de 8:00 a 10:00 am. Los hallazgos de la presente investigación proporcionan, a académicos y profesionales, una visión actualizada de cuáles son las variables que inciden en estos indicadores de reconocimiento y que, por consiguiente, conducen a estrategias de marketing en redes sociales más eficientes.

Companies use social media in their communication strategy to connect with their audiences via online brand communities and social media fan pages. In this context, the scientific community defines the term ‘engagement’ as the primary metric used to identify the degree to which brand and consumers are organically connected. This phenomenon gets measured by audience interactions with the brand content, which is the main factor stimulating participation and value perception in their relationship with the brand. Prior investigations show that the timing and duration of the messages published by the brand can predict the degree of social media engagement, however they do not provide the time and length patterns required for messages to increase engagement. For this purpose, we carried out a quantitative and descriptive content analysis of 14,067 Instagram posts from 14 Spanish brands across 10 industries. Findings allow us to conclude that brands are not fully optimising the scheduling of their timings during the working days and hours that drive the best level of interaction. Nonetheless, they do take advantage of the opportunity to publish longer messages to increase engagement. From a theorical and practical point of view, this analysis contributes to the understanding of the content factors that stimulate fan page engagement and provides guidelines for brand managers to efficiently define the content marketing strategy on Instagram.

The objective of this study was to identify university student profiles with different levels of predisposition and usage of digital competences in social communication and collaborative learning (CSCCL) as well as technology use in information search and treatment (CSTI). The sample comprised 383 students from three state universities in Spain. The study employed a questionnaire called “basic digital competences 2.0 in university students” (COBADI). Chi-squared automatic interaction detection (CHAID) algorithm was used for data analysis due to its capability to handle both quantitative and qualitative variables, enabling profiling and the generation of predictive models with easily interpretable graphical representations (decision trees). The results revealed a high level of digital competence in socialization and execution of tasks online, managing digital tools for planning study time, and using resources for information searching and browsing. These findings align with previous works on collaborative writing on the Internet and digital competence. However, students demonstrated low digital competence in data analysis processes and image production using social software apps, which has been linked to task complexity and heavy workload in other studies. Interestingly, the students’ sociodemographic characteristics (age, sex, and university attended) did not influence their predisposition towards the analyzed digital competences. In conclusion, enhancing effective digital teaching in higher education can be achieved by incorporating the teaching of critical analysis of information, addressing information overload, providing instruction on social software apps, and emphasizing collaborative learning. These strategies aim to help students acquire and apply knowledge relevant to the current job market.

The evaluation of teaching effectiveness in blended learning methodologies is usually carried out using Likert-type questionnaires; however, instruments with Behavioral Anchored Rating Scales (BARS) are sometimes employed for this purpose. This paper examines the validity and reliability of an instrument with BARS designed to assess teaching effectiveness in blended learning environments, within the university setting. The research involves a sample of 1436 students from a medium size university in Spain. Using this sample (n = 1436), the authors carry out a psychometric study that consists of four phases: (1) comprehension validity analysis, (2) construct validity analysis, (3) confirmation of construct validity, and (4) analysis of the instrument reliability. The findings provide satisfactory values for all the parameters analyzed (for instance: Variance explained = 77.61%; RMSEA = 0.042; or Cronbach’s alpha = 0.956), indicating that the BARS instrument examined is perfectly valid and reliable for the appraisal of teaching effectiveness in blended learning methodologies. The authors conclude that this paper fills an important gap in the literature by presenting an instrument that, thanks to the use of behavioral scales, facilitates this task in the university context.

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