Searching for LIS scholarly publications: A comparison of search results from Google, Google Scholar, EDS, and LISA

Pulikowski, Arkadiusz; Matysek, Anna

doi:10.1016/j.acalib.2021.102417

Cited by 12 publications

(10 citation statements)

References 32 publications

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“…Libraries frequently provide training resources to support users' efforts to adopt the most effective search terms and strategies on library databases [39], and similar resources should prove useful in facilitating the user efforts to utilize this potentially useful tool to the fullest extent. Also, in the experience of the authors toward the effective use of large language models outside of the context of the current study, "tinkering" with various search phrasings and gaining familiarity with its behavior have proven to be productive, and this approach is corroborated with research in information sciences, as well [40]. In other words, while these tools may provide relatively low barriers to entry, in order to fully utilize them, users may still need to gain sufficient proficiency [24].…”

Section: Discussionmentioning

confidence: 58%

AI-Supported Academic Advising: Exploring ChatGPT’s Current State and Future Potential toward Student Empowerment

Akiba,

Fraboni

2023

Education Sciences

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Artificial intelligence (AI), once a phenomenon primarily in the world of science fiction, has evolved rapidly in recent years, steadily infiltrating into our daily lives. ChatGPT, a freely accessible AI-powered large language model designed to generate human-like text responses to users, has been utilized in several areas, such as the healthcare industry, to facilitate interactive dissemination of information and decision-making. Academic advising has been essential in promoting success among university students, particularly those from disadvantaged backgrounds. Unfortunately, however, student advising has been marred with problems, with the availability and accessibility of adequate advising being among the hurdles. The current study explores how AI-powered tools like ChatGPT might serve to make academic advising more accessible, efficient, or effective. The authors compiled a list of questions frequently asked by current and prospective students in a teacher education bachelor’s degree program in the United States. Then, the questions were typed into the free version of ChatGPT, and the answers generated were explored and evaluated for their content and delivery. ChatGPT generated surprisingly high-quality answers, written in an authoritative yet supportive tone, and it was particularly adept at addressing general and open-ended career-related questions, such as career outlook, in a clear, comprehensive, and supportive manner using plain language. We argue that AI-powered tools, such as ChatGPT, may complement but not necessarily replace human academic advisers and that these tools may very well serve to promote educational equity by empowering individuals from a wide range of backgrounds with the means to initiate effective methods of seeking academic advice.

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Section: Discussionmentioning

confidence: 58%

AI-Supported Academic Advising: Exploring ChatGPT’s Current State and Future Potential toward Student Empowerment

Akiba,

Fraboni

2023

Education Sciences

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“…This study reviewed carpark and price index research indexed in Google Scholar. Previous research found that Google contained the most academic articles for each topic [20]. Google Scholar had the most significant percentage of citations in all fields of research (93%-96%), substantially more than Web of Science (WoS) (27%-73%) and Scopus (35%-77%) [21].…”

Section: Google Scholar Results From 1910 To 2019mentioning

confidence: 99%

Predicting Carpark Prices Indices in Hong Kong Using AutoML

Li¹,

Song²,

Li³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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The aims of this study were threefold: 1) study the research gap in carpark and price index via big data and natural language processing, 2) examine the research gap of carpark indices, and 3) construct carpark price indices via repeat sales methods and predict carpark indices via the AutoML. By researching the keyword "carpark" in Google Scholar, the largest electronic academic database that covers Web of Science and Scopus indexed articles, this study obtained 999 articles and book chapters from 1910 to 2019. It confirmed that most carpark research threw light on multi-storey carparks, management and ventilation systems, and reinforced concrete carparks. The most common research method was case studies. Regarding price index research, many previous studies focused on consumer, stock, press and futures, with many keywords being related to finance and economics. These indicated that there is no research predicting carpark price indices based on an AutoML approach. This study constructed repeat sales indices for 18 districts in Hong Kong by using 34,562 carpark transaction records from December 2009 to June 2019. Wanchai's carpark price was about four times that of Yuen Long's carpark price, indicating the considerable carpark price differences in Hong Kong. This research evidenced the features that affected the carpark price indices models most: gold price ranked the first in all 19 models; oil price or Link stock price ranked second depending on the district, and carpark affordability ranked third.

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“…They are provided with methodologies, methods and theoretical frameworks for studying exploratory search. Finally, this paper helps IS practitioners recognize the ubiquity of exploratory search activities in various ISs, for example, search engines (Khan et al , 2023; Pulikowski and Matysek, 2021), digital libraries (Barifah and Landoni, 2020; Hoeber and Shukla, 2022) and collaborative search systems (Andolina et al , 2018; Herceg et al , 2018). They can better appreciate the importance of certain design features in supporting exploratory search, thereby adapting their design strategies to develop exploratory search systems.…”

Section: Discussionmentioning

confidence: 99%

Exploratory search in information systems: a systematic review

Liu,

Qin,

Wang

et al. 2024

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Purpose Exploratory search activities are ubiquitous in various information systems. Much potentially useful or even serendipitous information is discovered during the exploratory search process. Given its irreplaceable role in information systems, exploratory search has attracted growing attention from the information system community. Since few studies have methodically reviewed current publications, researchers and practitioners are unable to take full advantage of existing achievements, which, in turn, limits their progress in this field. Through a literature review, this study aims to recapitulate important research topics of exploratory search in information systems, providing a research landscape of exploratory search. Design/methodology/approach Automatic and manual searches were performed on seven reputable databases to collect relevant literature published between January 2005 and July 2023. The literature pool contains 146 primary studies on exploratory search in information system research. Findings This study recapitulated five important topics of exploratory search, namely, conceptual frameworks, theoretical frameworks, influencing factors, design features and evaluation metrics. Moreover, this review revealed research gaps in current studies and proposed a knowledge framework and a research agenda for future studies. Originality/value This study has important implications for beginners to quickly get a snapshot of exploratory search studies, for researchers to re-align current research or discover new interesting issues, and for practitioners to design information systems that support exploratory search.

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Searching for LIS scholarly publications: A comparison of search results from Google, Google Scholar, EDS, and LISA

Cited by 12 publications

References 32 publications

AI-Supported Academic Advising: Exploring ChatGPT’s Current State and Future Potential toward Student Empowerment

AI-Supported Academic Advising: Exploring ChatGPT’s Current State and Future Potential toward Student Empowerment

Predicting Carpark Prices Indices in Hong Kong Using AutoML

Exploratory search in information systems: a systematic review

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