•A 1 mm thick mLHP module with 30 W cooling capacity was first developed.•A lowest system thermal resistance of 2 °C/W was obtained at 25 W.•Fan voltages and working orientations impact the ...performance indistinctively.•Cooling energy saved with the proposed module was up to 80%.•Coefficient of performance based on cooling power was increased by six times.
In this paper, an active air-cooling module based on a 1-mm-thick ultrathin miniature loop heat pipe with a flat evaporator for high-end ultra-slim laptop computers is presented and studied. Systematic experimental investigations were conducted under natural air convection and forced air cooling conditions with different fan voltages. The results indicated that the miniature loop heat pipe module could effectively dissipate a heat load of 12 W at all test orientations under natural convection with zero power consumption when the chip-junction temperatures were below 85 °C. Under forced air cooling, the proposed miniature loop heat pipe module had almost identical cooling performance at all test orientations when the fan input voltages were changed from 5 V to 2 V. Aided by infrared photography and theoretical analysis, the unique operation mechanism for the module was revealed. Finally, in a 35 °C temperature humidity chamber, the module could dissipate 25 W at a fan voltage of 5 V (22 W at 2 V) with the chip-junction temperature below 85 °C, showing a promising and energy-saving thermal management solution for high-end ultra-slim laptop computers. The results indicate that by using the proposed module, cooling energy savings of up to 80% could be realized compared to the current applied miniature heat pipe module in a laptop computer.
Laptops are commonplace in university classrooms. In light of cognitive psychology theory on costs associated with multitasking, we examined the effects of in-class laptop use on student learning in ...a simulated classroom. We found that participants who multitasked on a laptop during a lecture scored lower on a test compared to those who did not multitask, and participants who were in direct view of a multitasking peer scored lower on a test compared to those who were not. The results demonstrate that multitasking on a laptop poses a significant distraction to both users and fellow students and can be detrimental to comprehension of lecture content.
► We examined the detrimental effects of laptop multitasking on classroom learning. ► Learners who multitasked during class had reduced comprehension of lecture material. ► Learners in-view of multitaskers also had reduced comprehension of lecture material. ► Multitasking or being seated around multitaskers impedes classroom learning.
Over the past decade, the number of one-to-one laptop programs in schools has steadily increased. Despite the growth of such programs, there is little consensus about whether they contribute to ...improved educational outcomes. This article reviews 65 journal articles and 31 doctoral dissertations published from January 2001 to May 2015 to examine the effect of one-to-one laptop programs on teaching and learning in K-12 schools. A meta-analysis of 10 studies examines the impact of laptop programs on students' academic achievement, finding significantly positive average effect sizes in English, writing, mathematics, and science. In addition, the article summarizes the impact of laptop programs on more general teaching and learning processes and perceptions as reported in these studies, again noting generally positive findings.
The emergence of Life Cycle Assessment (LCA) on the global stage as a design and policy tool increases the importance of assessing and managing uncertainty. This article develops and implements ...uncertainty methods for hybrid LCA. Hybrid LCA combines a bottom–up construction of the supply-chain based on facility-level data on material/energy use with a top–down economic input–output (EIO) model to account for processes for which direct data were unavailable. For the bottom–up part of the LCA, we account for variability in process and usage pattern data by developing parameter ranges. For the EIO side we develop a method to assess price uncertainty. These methods are explored through a case study examining energy use and carbon dioxide emissions of manufacturing and use of a laptop computer, a 2001 Dell Inspiron 2500. Results show that manufacturing the computer requires 3010–4340 MJ of primary energy, 52–67% less than the energy to make a desktop computer, and emits 227–270 kg CO
2. The manufacturing phase represents 62–70% of total primary energy of manufacturing and operation. This indicates, as for desktop computers, that mitigating manufacturing energy use, for example through extending lifespan, can be an important strategy to manage the life cycle energy of laptop computers. Results also indicate that truncation error from excluded processes in the bottom–up process model is significant, perhaps particularly so due to complex supply chains of information technology products.
Students often have their own individual laptop computers in university classes, and researchers debate the potential benefits and drawbacks of laptop use. In the presented research, we used a ...combination of surveys and in-class observations to study how students use their laptops in an unmonitored and unrestricted class setting—a large lecture-based university class with nearly 3000 enrolled students. By analyzing computer use over the duration of long (165 min) classes, we demonstrate how computer use changes over time. The observations and student-reports provided similar descriptions of laptop activities. Note taking was the most common use for the computers, followed by the use of social media web sites. Overall, the data show that students engaged in off-task computer activities for nearly two-thirds of the time. An analysis of the frequency of the various laptop activities over time showed that engagement in individual activities varied significantly over the duration of the class.
•We studied laptop use in large classes using both surveys and classroom observations.•Type of laptop activity varied significantly over the duration of the long class.•Students used laptops for off-task activities nearly two-thirds of the time.•Note taking was the single most common laptop activity.
Many students use laptops to take notes in classes, but does using them impact later test performance? In a high-profile investigation comparing note-taking writing on paper versus typing on a laptop ...keyboard, Mueller and Oppenheimer (Psychological Science, 25, 1159—1168, 2014) concluded that taking notes by longhand is superior. We conducted a direct replication of Mueller and Oppenheimer (2014) and extended their work by including groups who took notes using eWriters and who did not take notes. Some trends suggested longhand superiority; however, performance did not consistently differ between any groups (experiments 1 and 2), including a group who did not take notes (experiment 2). Group differences were further decreased after students studied their notes (experiment 2). A meta-analysis (combining direct replications) of test performance revealed small (nonsignificant) effects favoring longhand. Based on the present outcomes and other available evidence, concluding which method is superior for improving the functions of note-taking seems premature.
Laptop computers are widely prevalent in university classrooms. Although laptops are a valuable tool, they offer access to a distracting temptation: the Internet. In the study reported here, we ...assessed the relationship between classroom performance and actual Internet usage for academic and nonacademic purposes. Students who were enrolled in an introductory psychology course logged into a proxy server that monitored their online activity during class. Past research relied on self-report, but the current methodology objectively measured time, frequency, and browsing history of participants' Internet usage. In addition, we assessed whether intelligence, motivation, and interest in course material could account for the relationship between Internet use and performance. Our results showed that nonacademic Internet use was common among students who brought laptops to class and was inversely related to class performance. This relationship was upheld after we accounted for motivation, interest, and intelligence. Class-related Internet use was not associated with a benefit to classroom performance.
The purpose of this study was to examine factors affecting teachers’ integration of laptops into classroom instruction. A research-based path model was tested based on data gathered from 379 K-12 ...school teachers to examine direct and indirect contributions of relevant institutional factors (overall support for school technology, technical support, and professional development) and teacher level factors (teacher readiness and teacher beliefs). The major premise of this study was that the hypothesized path model was powerful enough to explain a substantial amount of variance in teacher readiness (43%), beliefs (51%), and laptop integration (55%). The results suggest that teacher level factors (teacher readiness and teacher beliefs) strongly predict laptop integration, and that overall support for school technology and professional development have strong effects on teacher beliefs and readiness, respectively. All school-level factors also had a significant indirect impact on laptop integration, which is mediated by teacher readiness and beliefs.
We perform a global sensitivity analysis of the binding energy and the charge radius of the nucleus ^{16}O to identify the most influential low-energy constants in the next-to-next-to-leading order ...chiral Hamiltonian with two- and three-nucleon forces. For this purpose, we develop a subspace-projected coupled-cluster method using eigenvector continuation Frame D. et al., Phys. Rev. Lett. 121, 032501 (2018)PRLTAO0031-900710.1103/PhysRevLett.121.032501. With this method, we compute the binding energy and charge radius of ^{16}O at more than 10^{6} different values of the 16 low-energy constants in one hour on a standard laptop computer. For relatively small subspace projections, the root-mean-square error is about 1% compared to full-space coupled-cluster results. We find that 58(1)% of the variance in energy can be apportioned to a single contact term in the ^{3}S_{1} wave, whereas the radius depends sensitively on several low-energy constants and their higher-order correlations. The results identify the most important parameters for describing nuclear saturation and help prioritize efforts for uncertainty reduction of theoretical predictions. The achieved acceleration opens up an array of computational statistics analyses of the underlying description of the strong nuclear interaction in nuclei across the Segrè chart.
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