Sustainable Development Goals
Abstract/Objectives
"In the open online environment, people may actively search for information to read or passively to read information that is tweeted or shared by friends on social media. Besides printed texts, there are also multimodal texts including graphs, tables, animations, and videos. While reading these multi-modal and multi-source texts, people are facing challenges such as how to evaluate the source and evidence of the texts, how to infer the purpose of the author, how to perform effective search to avoid dependence on the engine’s recommendation, and how to learn amid the multi-source and multiple text reading. Based on the theory of an Integrated Framework of Multiple Text Use, this project will investigate university students’ multiple text reading from the preparation, execution, and production stages to provide possible effective intervention. With the advent of cloud-computing, artificial intelligence, and machine learning, the project centers on the three aims. 1. Develop a “Multiple Text Reading Interactive System” to enhance university students’ reflection and multiple text reading literacy via the system prompted epistemic metacognition monitoring and the interactive reading system. 2. Develop a “Multiple Text Reading Chatbot” based on the Messenger platform to prompt university students’ evaluation on the veracity, trustworthiness, and multiple justification process. 3. Apply Learning Analytics to investigate students’ multiple text reading process, human-machine interaction, and latent profiles behind the reading behaviors as well as associations among all the examined aspects. I hope to develop the above technology-enhanced epistemic tools to improve university students’ cognitive strategies, metacognitive strategies, and behaviors during their multiple text read. "
Results/Contributions

The ability to locate the desired information, evaluate the quality of the information, and synthesizing and comparing information across multiple sources has been regarded as multiple-text comprehension and as one of the 21st century competences. The current study will provide a browser-based epistemic prompt for students to reflect on the trustworthiness and relevance of the online texts and encourage them to constantly summarizing and comparing the materials they viewed in order to facilitate their English multimodal multiple text comprehension (MMTC). Specifically, we intended to ask the following three research questions.

1) How well do university students perform in their English MMTC?

2) What are learners’ cognitive and affective characteristics that predict university students’ English MMTC?

3) How will learners’ cognitive and affective characteristics moderate the epistemic prompting effect on learners’ English MMTC?

Participants were forty-eight university students from a psychology-related course. They participated in the study in return of partial credit for the course. 68.75% of the participants were female. Students’ were randomly assigned to the experiment group or the control group. The experiment group were provided with a browser-embedded note-taking device along with the epistemic prompting for students’ source evaluation. The control group were provided with the browser-embedded note-taking device only. Analysis results showed that learners MMTC performance was generally low. There was a statistically significant epistemic prompting effect on learners’ MMTC while learners’ English ability did not predict MMTC. Particularly, we found learners in the treatment group scored significantly lower than those in the control group. Implications of the study results were discussed regarding the intervention and instruction for MMTC among EFL learners in light of the cognitive load theory.

Keywords
multiple document readingepistemic promptinglearning analytics
References
1.

The link will direct readers to the relevant product of this project.

Contact Information
李元萱
yuanhsuanlee@mx.nthu.edu.tw