Schlagwort: Wikimedia Seite 1 von 5

@article{Crook2020,

title = {How internet essay mill websites portray the student experience of higher education},

author = {Charles Crook and Elizabeth Nixon},

url = {https://doi.org/10.1016/j.iheduc.2020.100775

https://www.sciencedirect.com/science/article/pii/S1096751620300518},

doi = {10.1016/j.iheduc.2020.100775},

issn = {1096-7516},

year  = {2020},

date = {2020-10-17},

journal = {The Internet and Higher Education},

volume = {48},

pages = {100775},

abstract = {Higher education is under mounting pressure to confront student practices of assignment outsourcing to internet services. The scale and buoyancy of this ‘essay mill’ industry has now been well documented, including its various marketing techniques for urging students to purchase bespoke academic work. However, the inherently suspect nature of such services demands that they adopt a particularly shrewd and empathic rhetoric to win custom from website visitors. In this paper, we investigate how such rhetoric currently constructs a critical version of the student's higher education experience. We present a thematic analysis of promotional text and images as found on a large sample of essay mill sites. Findings reveal how these sites promulgate a hostile and negative attitude towards higher educational practice. Yet these findings may also indicate where the higher education sector needs to reflect on its practice, not least in order to resist the toxic messages of essay mills.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Cromley2019,

title = {Drawing-to-Learn: Does Meta-Analysis Show Differences Between Technology-Based Drawing and Paper-and-Pencil Drawing?},

author = {Jennifer G. Cromley and Yang Du and Aygul Parpucu Dane},

editor = {Drawing-to-Learn: Does Meta-Analysis Show Differences Between Technology-Based Drawing and Paper-and-Pencil Drawing?},

url = {https://doi.org/10.1007/s10956-019-09807-6},

doi = {10.1007/s10956-019-09807-6},

year  = {2019},

date = {2019-12-21},

journal = {Journal of Science Education and Technology},

volume = {29},

pages = {216–229},

abstract = {Drawing-to-learn is a specific learning/reading strategy studied across many domains. In response to gaps in our knowledge about drawing-to-learn, we conducted a systematic meta-analysis of the literature published since the influential 2005 Van Meter and Garner literature review. We analyzed the benefits of directed learner-generated visual representations such as sketching, drawing, or computer-assisted creation of a full or partial static image. Forty-one peer-reviewed articles were screened in, together with 9 dissertations and 2 other documents; published from 2005 to 2018, these included 53 studies and 166 effects based on 8111 participants. The overall effect of drawing-to-learn across all dependent variable types (factual, inferential, and transfer) and both types of effects—comparing different types of drawing and comparing drawing to non-drawing conditions—was a significant g = 0.69. The overall effect was significant but differed across outcomes (g = 0.85 for factual, g = 0.44 for inferential, and g = 0.22 for transfer). Analyses across 6 moderators are presented. Not only does the literature continue to show that drawing-to-learn is better than the status quo, but directed drawing improves factual as well as inferential and transfer learning. Finally, researchers have found ways to improve drawing-to-learn instruction so that it can be even more effective than the simple directive to make a drawing.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}