Profiling low-proficiency science students in the Philippines using machine learning.

Filipino students' performance in global assessments of science literacy has always been low, and this was confirmed again in the PISA 2018, where Filipino learners' average science literacy scores ranked second to last among 78 countries. In this study, machine learning approaches were used to analyze PISA data from the student questionnaire to test models that best identify the poorest-performing Filipino students. The goal was to explore factors that could help identify the students who are vulnerable to very low achievement in science and that could indicate possible targets for reform in science education in the Philippines. The random forest classifier model was found to be the most accurate and more precise, and Shapley Additive Explanations indicated 15 variables that were most important in identifying the low-proficiency science students. The variables related to metacognitive awareness of reading strategies, social experiences in school, aspirations and pride about achievements, and family/home factors, include parents' characteristics and access to ICT with internet connections. The results of the factors highlight the importance of considering personal and contextual factors beyond the typical instructional and curricular factors that are the foci of science education reform in the Philippines, and some implications for programs and policies for science education reform are suggested.

The effects of search-irrelevant working memory content on visual search.

Previous experiments investigating visual search have shown that distractors that are semantically related to a search target can capture attention and slow the search process. In two experiments, we examine if distractors exactly matching, or semantically related to, search-irrelevant information held in working memory (WM) can also influence visual search while ruling out potential effects of color similarity. Participants first viewed and memorized an image of an everyday object, then they determined if a target item was present or absent in a two-object search array. On exact-match trials, the memorized object appeared as a distractor; on semantic-match trials, an object semantically related to the memorized object appeared as a distractor. Both exact-match and semantic-match distractors slowed search when the target was present in the search array. Our findings extend previous findings by demonstrating WM-driven attentional guidance by complex objects rather than simple features. The results also suggest that visual search can be influenced by distractors sharing only semantic features with a search-irrelevant, but active, WM representation.

Guidance of attention by information held in working memory.

Information held in working memory (WM) can guide attention during visual search. The authors of recent studies have interpreted the effect of holding verbal labels in WM as guidance of visual attention by semantic information. In a series of experiments, we tested how attention is influenced by visual features versus category-level information about complex objects held in WM. Participants either memorized an object's image or its category. While holding this information in memory, they searched for a target in a four-object search display. On exact-match trials, the memorized item reappeared as a distractor in the search display. On category-match trials, another exemplar of the memorized item appeared as a distractor. On neutral trials, none of the distractors were related to the memorized object. We found attentional guidance in visual search on both exact-match and category-match trials in Experiment 1, in which the exemplars were visually similar. When we controlled for visual similarity among the exemplars by using four possible exemplars (Exp. 2) or by using two exemplars rated as being visually dissimilar (Exp. 3), we found attentional guidance only on exact-match trials when participants memorized the object's image. The same pattern of results held when the target was invariant (Exps. 2-3) and when the target was defined semantically and varied in visual features (Exp. 4). The findings of these experiments suggest that attentional guidance by WM requires active visual information.