Annotate based on these instructions, tell me what to annotate and provide a comment for each annotation: Provide enough comments to indicate you read the entire article and were thoughtful about it. Feeling unsure what to say? Look over the slides from Week 1 "How to read a scientific article," and consider addressing these topics: 1) The major research question(s) explored. 2) What prior research was done? What research gaps does the author intend to fulfill? 3) What are their hypotheses? 4) How does the author address these gaps (i.e., methods)? 5) What's the main finding of each figure? 6) If you can choose, what is the ONE piece of data that was most important or directly addressing the question? 7) Do the author's interpretations match the evidence? (It's OK to disagree!) 8) Any critiques or further comments on the paper.

Cognitive Load During Web Searches In the context of web search, the need to identify relevant information is related to a higher ECL, such as when a person encounters an interesting article irrelevant to the task at hand [31]. High (CL can occur when websites do not present information im a direct manner or when the webpage has a bot of complex interactive elements to it, which the person needs to navigate in order to get to the desired information [32]. The ICL also depends on the person's domain knowledge that helps them organize the information accordingly [33]. Finally, higher GCL occurs when 8 person is actively collecting and synthesizing information from various sources,as they engage in processes thal enhance their understanding and coniribule to knowledge construction [34, 35]. High intrinsic load and extraneous load can impair beaming, while germane load enhances it. Cognitive load fluctuates across different stages of the web search process, with query formulation and relevance judgment being particularly demanding [36]. During query formulation, users must recall specific terms and concepts, engaging heavily with working memory and long-term memory to construct queries that yield relevant results. This phase is associated with higher cognitive load compared to tasks such as scanning search result pages, which rely more on recognition rather than recall. Additionally, the reliance on search engines for information retrieval, known as the "Google Effect,\" can shift cognitive efforts from information retention to more extemalized memory processes [37]. Namely, as users increasingly depand on search engines for fact-checking and accessing information, their ability to remember specific content may decline, although they retain a strong recall of how aind where to find it. The design and organization of search engine resull pages significantly influence cognitive load during information retrieval. The inclusion of multiple compositions, such as ads, can overwhelm users by dividing their attention across competing elements [38]. When tasks, such as web searches, present excessive complexity or poorly designed interfaces, they can lead to a mismaich between user capabilities and environmental demands [38]. Individual differences in cognitive capacity and search expertise significantly influence how users experience cognitive load during web searches. Participants with higher working memary Capacity and cognitive flexibility are better equipped to manage the demands of complex tasks, such as formulating queries and synthesizing information from multiple sources [39]. Experienced users (those familiar with search engines) often perceive lasks as less challenging and demonstrate greater efficiency in navigating ambiguous or fragmented information [39]. However, even skilled users encounter elevated cognitive load when faced with poorly designed interfaces or tasks requiring significant recall over recognition [39]. Behaviors like high revisit ratios (returning frequently to previously visited pages) are also present regardless of experience level; they are linked to increased cognitive strain and lower task efficiency [39]. To mitigate cognitive load, in addition to streamlining the weer interface and flow designers can incorporate contextual support and features that provide semantic information alongside search results. For example, displaying related terms or categorical labels beside search result lists can 14 reduce mental demands during critical stages like query formulation and relevance assessment [36]