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3.2. Participants
Participants consisted of 214 non-full-time undergraduate students from the Faculty
of Economics, Hanoi Open University, including those majoring in e-commerce,
accounting, and business administration.
Participants ranged in age from 18 to 24 years old, with a mean age of 20.6 years.
Approximately 56% of participants identified as female, while 44% identified as male.
All participants reported regular use of digital devices for academic purposes and
indicated that they had used at least one AI-based academic tool during the previous
semester.
3.3. Instruments
Three instruments were used to collect data:
Digital Media Consumption Scale (DMCS)
This questionnaire assessed the average daily time students spent on digital
platforms, particularly short-form video content and social media feeds. The scale
included items measuring multitasking behaviors, frequency of platform switching, and
perceived attention fragmentation.
AI-Assisted Learning Usage Inventory (AILUI)
This instrument was designed to evaluate how frequently students used AI tools for
a range of academic tasks. These included generating written responses, summarizing
academic texts, brainstorming ideas, and receiving feedback on assignments. To capture
the extent of usage, participants’ responses were measured using a five-point Likert scale,
allowing for a systematic assessment of how often these tools were utilized in their
learning activities.Deep Thinking Assessment Task (DTAT)
The DTAT required participants to produce a structured analytical essay in response
to a complex social issue, thereby assessing their capacity for higher-order thinking. The
essays were evaluated using a detailed rubric that focused on several key criteria,
including depth of analysis, which reflects the ability to explore issues critically; argument
coherence, referring to the logical organization and clarity of ideas; integration of
evidence, which measures how effectively supporting information is incorporated; and
originality of reasoning, indicating the extent to which participants demonstrate
independent and creative thought.Each essay was scored by two independent raters to
ensure reliability.
3.4. Procedure
Data collection was conducted in two stages. In the first stage, students completed
the DMCS and AILUI questionnaires online. In the second stage, selected participants
completed the DTAT writing task in a controlled environment to minimize digital
distractions.
Following the writing task, twenty participants were selected for semi-structured
interviews to explore their experiences with AI tools and their perceptions of how digital
media affected their ability to concentrate on academic tasks.
3.5. Data analysis
Quantitative data were analyzed using descriptive statistics and Pearson correlation
analysis. Independent samples t-tests were used to examine differences in deep thinking
performance between high-frequency and low-frequency users of digital media and AI.
Qualitative interview data were analyzed using thematic analysis following Braun
and Clarke’s (2006) methodology, allowing recurring themes related to cognitive
engagement and technology use to emerge from the data.

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