2020
DOI: 10.1016/j.compedu.2020.103809
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Identifying multiple learning spaces within a single teacher-focused Twitter hashtag

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Cited by 64 publications
(61 citation statements)
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References 48 publications
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“…As examples, Kelchen, Rosinger, and Ortagus (2019) demonstrated how data on statelevel educational policies in the United States could be joined to data on student outcomes to compare the effects of different policies between states, and Rosenberg et al (2016) combined data on how many public school teachers were employed in each state in the United States with social media data to understand the activity of participants in one of 47 state-based educational Twitter hashtags. These new combined datasets can give rise to exploratory bottom-up analyses as well; differences between states in participants' activity sparked a study of the activity of regularly-occurring Twitter chats (Greenhalgh et al, 2020). Such dataset combinations may require new types of skills from the dimensions of computer science and statistics to integrate and analyze the data correctly, and will likely also require the addition of researchers with more diverse knowledge bases relating to teaching, learning, and educational systems than are needed by single-data-type studies.…”
Section: Data Science In Education: Data Science As a Methodologymentioning
confidence: 99%
See 1 more Smart Citation
“…As examples, Kelchen, Rosinger, and Ortagus (2019) demonstrated how data on statelevel educational policies in the United States could be joined to data on student outcomes to compare the effects of different policies between states, and Rosenberg et al (2016) combined data on how many public school teachers were employed in each state in the United States with social media data to understand the activity of participants in one of 47 state-based educational Twitter hashtags. These new combined datasets can give rise to exploratory bottom-up analyses as well; differences between states in participants' activity sparked a study of the activity of regularly-occurring Twitter chats (Greenhalgh et al, 2020). Such dataset combinations may require new types of skills from the dimensions of computer science and statistics to integrate and analyze the data correctly, and will likely also require the addition of researchers with more diverse knowledge bases relating to teaching, learning, and educational systems than are needed by single-data-type studies.…”
Section: Data Science In Education: Data Science As a Methodologymentioning
confidence: 99%
“…LDT scholars have been at the forefront of efforts to identify ways to address new and long-standing questions using novel data sources. For example, LDT researchers have found ways to utilize novel datasets from social media to understand the role of social media in teaching and learning (Coughlan, 2019;Greenhalgh et al, 2020;Kimmons & Smith, 2019;Romero-Hall et al, 2018), use telemetric data collected as students interact with educational technology to gain insight into students' motivation and learning (e.g., Bernacki et al, 2015;Peddycord-Liu et al, 2018;Rodriguez et al, 2019), and use datasets from wearable devices to engage and understand the learning of K-12 students about data analysis and interpretation (Lee et al, 2015). However, the LDT field's creative integration of novel datasets also brings with it new challenges.…”
Section: Introductionmentioning
confidence: 99%
“…After the directives of the teacher, the students started using the same hashtag. A hashtag is an affinity space that allows users to keep their discussions connected, and they can make moves back and forth between tweets (Greenhalgh, Rosenberg, Willet, Koehler, & Akcaoglu, 2020).…”
Section: The Use Of Hashtagmentioning
confidence: 99%
“…This incongruence between the actual production and the perception of the use of Twitter may have resulted from insufficient knowledge of using Twitter in writing. As Greenhalgh et al (2020) argued, students' familiarity with the use of Twitter's different features is necessary in order for them to benefit from Twitter-based learning.…”
Section: The Students' Views About the Use Of Twitter In Their Writinmentioning
confidence: 99%
“…LDT scholars have been at the forefront of efforts to identify ways to address new and long-standing questions using novel data sources. For example, LDT researchers have found ways to utilize novel datasets from social media to understand the role of social media in teaching and learning (Coughlan, 2019;Greenhalgh et al, 2020;Kimmons & Smith, 2019;Romero-Hall et al, 2018), use telemetric data collected as students interact with educational technology to gain insight into students' motivation and learning (e.g., Bernacki et al, 2015;Peddycord-Liu et al, 2018;Rodriguez et al, 2019), and use datasets from wearable devices to engage and understand the learning of K-12 students about data analysis and interpretation (Lee et al, 2015).…”
Section: Introductionmentioning
confidence: 99%