Academic Progress
Academic Progress - Related Videos
02:07
Tumor Progression
0 Views •
2023
Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages. Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
02:07
Tumor Progression
0 Views •
2021
Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages. Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
09:25
Bioluminescent Orthotopic Model of Pancreatic Cancer Progression
0 Views •
Cited by 34 •
2013
Improved understanding of pancreatic cancer biology is critically needed to enable the development of better therapeutic options to treat pancreatic cancer. To address this need, we demonstrate an orthotopic model of pancreatic cancer that permits non-invasive monitoring of cancer progression using in vivo bioluminescence imaging.
11:16
Progressive-ratio Responding for Palatable High-fat and High-sugar Food in Mice
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Cited by 70 •
2012
The present report details the protocol employed to measure the rewarding effects of high-fat food in mice using a progressive ratio operant conditioning task.
03:03
mTOR Signaling and Cancer Progression
0 Views •
2023
The mammalian target of rapamycin or mTOR protein was discovered in 1994 due to its direct interaction with rapamycin. The protein gets its name from a yeast homolog called TOR. The mTOR protein complex in mammalian cells plays a major role in balancing anabolic processes such as the synthesis of proteins, lipids, and nucleotides and catabolic processes, such as autophagy in response to environmental cues, such as availability of nutrients and growth factors. The mTOR pathway or the...
FAQs
Averages provide a central summary of student performance, while percentages express outcomes such as course completion or attendance in a comparable form. Examining these measures across different points in time can show whether performance is improving, stable, or declining. Used together, they give decision-makers a concise view of broad academic patterns without relying on a single student result.
Distributions show how academic results are spread across students rather than reducing performance to one average. They can reveal whether outcomes cluster closely together or differ substantially, helping analysts recognize variation within a group. This perspective matters because a stable average may conceal persistent gaps or markedly different experiences among students.
Comparing measures across time identifies trends, whereas comparing groups highlights differences in outcomes or participation. Interpreting both comparisons alongside variation helps distinguish broad improvement from changes affecting only some students. These analyses can expose persistent gaps, indicate where performance has shifted, and provide a more informative picture than examining one test score or grade alone.
Useful evaluation begins with measures supported by the educational setting, including test scores, grades, course completion, and attendance. Analysts can organize these observations by time period or student group, then summarize them with averages, percentages, distributions, and comparisons. This workflow turns separate records into evidence that can be examined for trends, gaps, and changes in performance.
Regular statistical review can draw attention to declining performance, persistent gaps, or other unfavorable patterns before they become less visible in overall results. Comparing current measures with earlier results or with other groups helps locate areas requiring attention. Educators can then use that evidence to inform instructional responses and focus support where the observed outcomes indicate a need.
Program assessment uses summarized academic measures and comparisons to examine whether outcomes change across time or differ among groups. Test scores, grades, completion, and attendance can provide several perspectives on program-related results rather than relying on one indicator. Findings support evidence-based instructional planning and more informed educational decisions, while variation among students remains part of the interpretation.