ai scholarship essay writers

ai scholarship essay writers

The Impact of AI on Scholarship Essay Writing

1. Introduction

Despite the growth of automation, it does not necessarily mean that the generations of scholars will have to fully depend on using AI to assist their studies. Like any system, AI also has its flaws and limitations. Some of the more complex and nuanced parts of natural language can be beyond the understanding of some tools, and the heavy reliance on machines may sacrifice accuracy and quality for the sake of convenience. Feedback from AI systems may also prove to be less a form of guidance and more a direct correction tool. It could take away a student’s chances of learning from their own mistakes and discoveries. This could lead to a backlash for the education system to favor the old traditions over the modernization.

In the coming years, we are worried that there will be fewer opportunities for students to use and develop their writing skills because there will be an increase of machines marking examinations and essays in online modules. This may lead to a generation of students whose writing abilities are not as advanced as students receiving tuition from the professionals. At present, the implications of automation are not being applied to their full potential. Most students submit assessments and receive feedback using Turnitin through an online module, a machine-generated report of their assessment which will indicate where a resource has been referenced and whether it is duplicated content from other sources. At present, Turnitin is not advanced enough to provide an overall grade for an assignment due to variances in style and content, although this may change in the coming years.

AI is defined as the study and design of intelligent agents. Robots and AI systems (although at a very low level of intelligence) have been with us for many years. Sophisticated AI is exemplified by Deep Blue, a chess playing computer which beat world champion Garry Kasparov, and Watson, a question answering system which beat the human competitors of TV game show Jeopardy.

2. Advantages of AI in Scholarship Essay Writing

Improve the effectiveness of note-taking and information retention. Students generally perform better on assessments when allowed to use notes. Note-taking, whether verbatim or in “own words,” is an effective way to encode information for later review. Note-taking organizes information for encoding, and organized encoded information is easier to retrieve than disorganized information. Unfortunately, students are not given useful strategies for note-taking and in many cases are simply told to “take notes.” A recent experiment with a new note-taking strategy was designed to increase student engagement with notes and test the hypothesis that low-achieving students might benefit from being told to take notes. Given a text to read and a set of questions on that text, students were randomly assigned one of two note-taking conditions. The “low-choice” condition group was simply told to re-read the passage and take notes focusing on the notes’ future usefulness for themselves or for someone else studying the same passage later. The “high-choice” condition group participated in three note-taking decision activities in addition to note-taking. The activities and the notes were intended to increase the salience of the note-taking strategy and to increase the value of notes for later review. These students learned to focus their notes on what was most testable in the material, develop organizational components to their notes which were aimed at improving test success, and predict potential test questions and answers and prepare the notes to be useful for answering those questions. All students returned a week later to take a test on the passage. Both the high- and low-achieving students in the activities condition outperformed those in the notes condition and achieved equivalent results to the low-achieving students not in the activities condition. This strategy may be especially effective for low-achieving students who have to be taught how to “multiply the value of effort by direction” with learning strategies in order to level the playing field with high-achieving students. A digital tool for creating and organizing notes such as Livescribe or Evernote is a powerful way of developing these note-taking skills. Students employing this strategy now have an essay and notes that are ready to construct an outline for an essay. All of these tools increase the generativity of the student’s retrieval at later test or writing time, all in aid of achieving the goal to write a good essay.

3. Challenges and Ethical Considerations

AI has the potential to strongly impact automated essay evaluation. With the current dominance of supervised machine learning, the systems are only as good as the tools used to evaluate them. If the assessments from students or instructors are poor, the system could learn from incorrect or undesired attributes, and provide biased feedback. This may actually hinder the effectiveness of writing instruction and result in students not using the feedback systems. Additionally, if the AES is to be used as a grading tool, then students could potentially ‘game the system’ by writing essays specifically designed to fool the automated evaluation, rather than using their skills to write the best essay. If the system is to be used in high-stakes situations, it would be beneficial to have an unsupervised form of machine learning to ensure that the assessment criteria is universal and is not influenced by the reliability of human grading. This would be a significant challenge but has potential to improve over what can be achieved with human assessment. An extension to this would be using a form of AES to assess and train non-native speakers of a language to improve their writing skills. An oft-cited ethical consideration with AES regards the diagnostic capabilities of the systems, and the potential impact on student confidence and self-esteem. This is particularly significant in the case of students with learning disabilities or those who are already reluctant writers. AES has the potential to provide very detailed and accurate feedback on the strengths and weaknesses of an essay, however sometimes the damage of highlighting negatives may outweigh the benefit. Research has shown that teachers of lower grade students tend to avoid giving feedback that corrects mistakes, because children in general do not react well to criticism. A system which simply highlights errors without cause may be counter-productive in the case of students who lack motivation to write. Steps would need to be taken to ensure that the feedback provided to any student is always beneficial to the overall improvement of their writing skills, and does not discourage them from further efforts. Another diagnostic concern involves the possibility of using AES to identify markers of certain conditions or undesirable personality traits in the writings of individuals. This would be aimed not at improving the writing skills of the individuals, but rather to assist in prediction of future behaviours or to make inferences about the capabilities of the individuals in question. This could have serious implications in terms of privacy and stigma on labelled individuals, and would need to be strongly regulated to prevent misuse.

Section “3. Challenges and Ethical Considerations”.

4. The Future of AI in Scholarship Essay Writing

The future potential of AI in essay assistance is substantial. As older AI tools like input methods or grammar/spell checkers become more useful and easily available, the increasingly difficult problems in writing scholarship essays will rise. By the time these problems arise, new AI methods or existing methods implemented in new ways will be ready. These issues include purposeful manipulation of syntactical rules and rare usage of complex sentence structures, something that grammar/spell checkers are still quite poor at identifying. In a given essay, syntax and structure must be analyzed in depth to receive a characterization of writing style. Writing style is frequently judged on essay contest entries and scholarships. This often occurs without a formal definition of what writing style is; such judges assume it is known. A characterization usually consists of the attributes of a thing, how it is defined, and examples of it. AI syntax analysis would be able to provide a purposeful definition of various complex sentence structures and an example of their use from the essay. This would give AI programmers concrete ways to replicate said style in the future. A methodology for analyzing attributes was shown in a project done by Michael Elhadad and was quite successful for the complexity of writing style analysis mentioned in his post-graduate work at the Department of Medical Informatics, Rouen University, France. At that time, his project exceeded the AI technology available to him. In the future, chat or IM-based interfaces may be replaced by spoken language interpreters. This would help disabled persons in need of a scholarship get extra assistance. Also, the input methods mentioned will be obsolete and replaced by pattern recognition systems tied directly to a CNS response.

There are already intelligent business aids, such as Mobius, that offer reliable answers to economic and statistical queries. Another version of AI, known as TABARI, is a program that can record as data all events that happen in a given text and process that data into a plot summary that significantly condenses the space taken up by the actual events. This form of condensation will likely become particularly useful in the future of textual analysis. Currently, the pace of certain professional and college-level courses may deter students from reading the entire assignment. Instead, they will read critiques and analyses of the text from secondary sources. AI programs that generate instant plot summaries and abstracts could give such students useful information from the text without them having to process and condense it themselves. This will give them an incentive to at least examine the primary citation and possibly increase a student’s cognitive ability.

5. Conclusion

AI is an astonishing innovation and it is ending up progressively across the board in the public eye. The advancements in AI have increased monstrous ground in the course of recent years. Due to this development, it has caused a worry whether or not the content given by AI is advantageous to people. One of the real contentions occurs if AI can give sufficient help to relax without human contribution. This examination embarks to distinguish the pertinence of AI-produced data to online education for leisure through an exploratory research program. This finds that AI-produced data is very pertinent to students, giving it is anything but difficult to get to and enormous in amount. It is additionally anything but difficult to peruse and very little of concentrated. Although the data was created without human contribution, it shares a wide assortment of presumption, perspective, and conclusion which can invigorate basic learning by the student. From this, we can derive AI-produced data can sufficiently help casual online education.