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This chapter examines the micro-level dynamics of cross-innovation involving audiovisual and educational expertise through the prism of two cases: an augmented reality-based chemistry learning app developed in Estonia and a 360-degree short film project aimed at documenting and raising awareness about historical buildings in Lithuania. Based on the two cases, the chapter outlines several trends: the broadening of the notion of education beyond institutional education; the growing interest in public–private partnerships; and the emergence of heterogeneous networks feeding into the larger epistemic community of educational innovators. It also highlights a number of challenges that members of this community may face, including institutional resistance to change, schools’ lack of resources, teachers’ and administrators’ reluctance to use new technology and emerging technologies’ lack of maturity.

The purpose of this paper is to describe a proposal for a data-driven investigation aimed at determining whether students’ learning behavior can be extracted and visualized from action logs recorded by Moodle. The paper also tried to show whether there is a correlation between the activity level of students in online environments and their academic performance with respect to final grade.

The analysis was carried out using log data obtained from various courses dispensed in a university using a Moodle platform. The study also collected demographic profiles of students and compared them with their activity level in order to analyze how these attributes affect students’ level of activity in the online environment.

This work has shown that data mining algorithm like vector space model can be used to aggregate the action logs of students and quantify it into a single numeric value that can be used to generate visualizations of students’ level of activity. The current investigation indicates that there is a lot of variability in terms of the correlation between these two variables.

The value presented in the study can help instructors monitor course progression and enable them to rapidly identify which students are not performing well and adjust their pedagogical strategies accordingly.

A plan to continue the work by developing a complete dashboard style interface that instructors can use is already underway. More data need to be collected and more advanced processing tools are necessary in order to obtain a better perspective on this issue.

This study aims to investigate the technology usage behaviour of the tourists in line with the modified unified theory of acceptance and use of technology (UTAUT) model.

Data were collected from a survey of 265 tourists using the random sampling technique. Partial least squares-based structural equation modelling (PLS-SEM) technique was used to analyze the data.

The findings revealed that performance expectancy, hedonic motivation and habit significantly influence the behavioural intention of tourists to use information and communication technology (ICT), while effort expectancy, social influence, and facilitating conditions do not have a significant influence. However, actual ICT usage behaviour largely depends on the behavioural intention of the tourists, and their habits, while the facilitating conditions do not have any influence in this case.

The findings uncover the core factors influencing tourists' actual ICT use behaviour that can assist the concerned stakeholders in designing tourism planning and sales. The study results also offer pathways for the world's tourism industry for a healthy recovery from the COVID-19 pandemic.

The findings have made robust contributions by extending the existing UTAUT-based literature by adding two new moderators in the relationship between behavioural intention and actual ICT usage behaviour.

This study aims to analyze the factors that drive purchases via Instagram and contribute to the growth of Instagram Commerce and examine the moderating role of gender, age and experience in Instagram use in the proposed relationship between six variables derived from commitment–trust theory, the technology acceptance model and consumer decision-making theory.

A survey was completed by respondents after watching a video about Instagram Commerce. A total of 404 valid responses were collected. The research model was analyzed using partial least squares structural equation modeling.

This study makes numerous contributions to Instagram Commerce and holds significant implications for professionals in the social commerce field. Among other results, we found that trust, attitude, perceived usefulness and alternative evaluation significantly affected consumers’ purchase intentions. However, this study found no relationship between trust or ease of use and purchase intention. Finally, it demonstrates the moderating role of gender, age and experience on some of these relationships.

This research centers on an analysis of consumer purchase behavior on Instagram Commerce, taking a highly innovative approach. The particular originality of this study lies in the proposed model of adoption of social commerce via Instagram, based on a critical framework. This study also provides an original analysis of the moderating effect of the classification variables: gender, age and experience in Instagram use.

Factores que impulsan la intención de compra en Istagram Commerce

Resumen

Los objetivos de la presente investigación son (i) analizar los factores que impulsan las compras a través de Instagram y contribuyen al crecimiento del comercio en Instagram y (ii) examinar el papel moderador del género, la edad y la experiencia en el uso de Instagram sobre la relación propuesta a partir de seis variables derivadas de la Teoría del Compromiso-Confianza, el modelo TAM y la Teoría de la Toma de Decisiones del Consumidor.

Los encuestados completaron una encuesta después de ver un vídeo sobre Instagram Commerce. Se recogieron un total de 404 respuestas válidas. El modelo de investigación se analizó mediante un modelo de ecuaciones estructurales de mínimos cuadrados parciales.

El presente estudio hace numerosas contribuciones al Instagram Commerce y tiene importantes implicaciones para los profesionales del campo del comercio social. Entre otros resultados, encontramos que la confianza, la actitud, la utilidad percibida y la evaluación alternativa afectan significativamente a las intenciones de compra de los consumidores. Sin embargo, este estudio no encontró ninguna relación entre la confianza o la facilidad de uso y la intención de compra. Por último, se demuestra el papel moderador del género, la edad y la experiencia en algunas de estas relaciones.

Esta investigación se centra en un análisis del comportamiento de compra de los consumidores en Instagram Commerce, adoptando un enfoque muy innovador. La originalidad particular del trabajo radica en la propuesta de un modelo de adopción del comercio social a través de Instagram, basado en un marco crítico. El estudio también proporciona un análisis original del efecto moderador de las variables de clasificación: género, edad y experiencia en el uso de Instagram.

本研究的目的是(i)分析推动通过Instagram购买并促进Instagram商务发展的因素; (ii)研究性别、年龄和使用Instagram的经验对源自承诺-信任理论、TAM模型和消费者决策理论的六个变量之间的拟议关系的调节作用。

受访者在观看了有关Instagram商业的视频后完成了一项调查。共收集到404份有效的回复。研究模型采用偏最小二乘法结构方程模型进行分析。

本研究对Instagram商务做出了许多贡献, 并对社交商务领域的专业人士具有重要意义。在其他结果中, 我们发现信任、态度、感知有用性和替代性评价对消费者的购买意向有显著影响。然而, 本研究发现信任或易用性与购买意向之间没有关系。最后, 它证明了性别、年龄和经验对其中一些关系的调节作用。

这项研究以分析消费者在Instagram商务上的购买行为为中心, 采取了一种高度创新的方法。这项研究的独特之处在于提出了一个基于批判性框架的通过Instagram进行社交商务的模型。该研究还对分类变量的调节作用进行了原创性分析：性别、年龄和使用Instagram的经验。