RECIPE: How to Integrate ChatGPT into EFL Writing Education

The integration of generative AI in the field of education is actively being explored. In particular, ChatGPT has garnered significant interest, offering an opportunity to examine its effectiveness in English as a foreign language (EFL) education. To address this need, we present a novel learning platform called RECIPE (Revising an Essay with ChatGPT on an Interactive Platform for EFL learners). Our platform features two types of prompts that facilitate conversations between ChatGPT and students: (1) a hidden prompt for ChatGPT to take an EFL teacher role and (2) an open prompt for students to initiate a dialogue with a self-written summary of what they have learned. We deployed this platform for 213 undergraduate and graduate students enrolled in EFL writing courses and seven instructors. For this study, we collect students' interaction data from RECIPE, including students' perceptions and usage of the platform, and user scenarios are examined with the data. We also conduct a focus group interview with six students and an individual interview with one EFL instructor to explore design opportunities for leveraging generative AI models in the field of EFL education

Understanding the Performance Characteristics of Computational Storage Drives: A Case Study with SmartSSD

The emerging computational storage drives (CSDs) provide new opportunities by moving data computation closer to the storage. Performing computation within storage drives enables data pre/post-processing without expensive data transfers. Moreover, large amounts of data can be processed in parallel thanks to the nature of the field-programmable gate array (FPGA) included in CSDs. In a CSD, there are several implementation techniques that support parallel processing, each of which provides a different degree of parallelism. However, without sufficient understanding of the parallel processing techniques of CSD, it can lead to overhead due to misuse rather than benefiting from task offloading. Thus, to exploit the best performance of CSDs, it is important to properly adjust the degree of parallelism of each implementation technique. In this paper, we focus on the study of the differences in CSD performance according to various combinations of parallel processing techniques. To investigate the performance differences, we implement and offload the data verification algorithm to the CSD and analyze the performance and resource utilization. The experimental results show that implementing the data verification algorithm with a sufficient understanding of CSD’s parallel processing techniques can improve the performance by up to 20 times. Moreover, even with the same degree of parallelism, the performance can differ by 59% depending on the combination of implementation techniques. These results imply that proper orchestration of different implementation techniques leads to better performance and efficient resource utilization

Understanding University Students’ Experiences, Perceptions, and Attitudes Toward Peers Displaying Mental Health–Related Problems on Social Networking Sites: Online Survey and Interview Study

BackgroundCollege students’ mental health is at an all-time low. Students are increasingly disclosing their vulnerable, stigmatizing experiences on online social networking sites (SNSs). Peer support facilitated by SNSs can play a crucial role for the students in coping with mental health–related problems. Thus, it is imperative to understand how university students form perceptions, attitudes, and behaviors toward their peers who are dealing with mental health problems. ObjectiveThis study aimed to provide a better understanding of how college students recognize, perceive, and react to signs of mental health problems in their peers on SNSs. Our ultimate goal in this study was to inform the design of SNSs that can facilitate online peer support. MethodsWe conducted surveys with 226 students as well as semistructured interviews with 20 students at six universities in South Korea. ResultsOf the 226 survey respondents, 150 (66.4%) reported that they recognized signs of a mental health problem on their friends’ SNS posts. However, a considerable number of respondents (62/150, 41.3%) were reluctant to offer support, even when they had identified friends who were at risk; this reluctance was due to a lack of knowledge or confidence and their desire to maintain a distance from at-risk peers to save their identity from stigmatization and to avoid emotional contagion online. ConclusionsDrawing on these results, we provide implications that could explain the construction of students’ perceptions regarding their peers’ mental health problems. We also provide design proposals for SNSs to serve as platforms that facilitate just-in-time and adaptive support exchanges among peers while mitigating stigma-related concerns

An I/O isolation scheme for key-value store on multiple solid-state drives

© 2019 IEEE.High-performance storage devices, such as Non-Volatile Memory express Solid-State Drives (NVMe SSDs), have widely adopted in data centers. Especially, multiple storage devices improve higher I/O performance compared with a single device. However, the performance can be reduced in the case of workloads with mixed read and write requests (e.g., key-value stores) even though multiple storage devices are adopted. The reason is that read requests can be blocked until the processing for write requests is finished. In this paper, we propose an I/O isolation scheme to improve the performance of key-value store for multiple SSDs. In our scheme, we separate read and write operations for multiple files. For example, we classify generated files of key-value store and perform read/write operations in the separated storage devices according to the characteristics of each file. To do this, we deploy files by considering their characteristics on multiple SSDs. We implement our scheme in RocksDB and evaluate its performance with six NVMe SSDs compare with RAID-0 configuration. In the experimental results, we demonstrate that our scheme improves performance compared with an existing scheme (i.e., RAID-0).N

An efficient database backup and recovery scheme using write-ahead logging

© 2020 IEEE.Many cloud services perform periodic database backup to keep the data safe from failures such as sudden system crashes. In the database system, two techniques are widely used for data backup and recovery: A physical backup and a logical backup. The physical backup uses raw data by copying the files in the database, whereas the logical backup extracts data from the database and dumps it into separated files as a sequence of query statements. Both techniques support a full backup strategy that contains data of the entire database and incremental backup strategy that contains changed data since a previous backup. However, both strategies require additional I/O operations to perform the backup and need a long time to restore a backup. In this paper, we propose an efficient backup and recovery scheme by exploiting write-ahead logging (WAL) in database systems. In the proposed scheme, for backup, we devise a backup system to use log data generated by the existing WAL to eliminate the additional I/O operations. To restore a backup, we utilize and optimize the existing crash recovery procedure of WAL to reduce recovery time. For example, we divide the recovery range and applying the backup data for each range independently via multiple threads. We implement our scheme in MySQL, a popular database management system. The experimental result demonstrates that the proposed scheme provides instant backup while reducing recovery time compared with the existing schemes.N

Design Constraints and Their Influence upon Design Outcome

Background: The Effect of two design constraints, ergonomic and aesthetic, on conceptual design ideation and development was investigated. The chosen constraints were selected as experimental conditions to understand the influence of design constraints more generally on concept design. Methods: Workshops were held with participant designers who provided the two constraints (ergonomics and aesthetics). Design outcomes were then assessed by both a sample of potential users and design experts. Results: The results indicated that ergonomic, rather than aesthetic, constraints resulted in radically new ideas. Aesthetic outcomes indicated a highly figurative process, resulting in appropriate, yet less novel solutions. Critical function failure was also identified in ergonomic derived outcomes. Conclusions: The provision of ergonomic design constraints provided a foundation for the emergence of more novel product design solutions. However, aesthetic derived concepts were assessed as more appropriate in terms of both form and function. The appropriation of ergonomic constraints may provide greater scope for novel design solutions but only if functional expectations are satisfied. Aesthetic design constraints stimulated analogous and metaphoric design approaches. Thus, the results indicate how the provision of differing constraints implicated design outcomes