Volunteering for the college entrance examination is an important decision faced by candidates and parents, and the emergence of AI volunteer filling tools has brought new hope to this process. This paper tests mainstream AI volunteer filling tools such as Baidu, Quark, and QQ Browser, and discusses the performance of these tools in terms of information richness, personalized recommendations, and complex demand solving capabilities.
It is not new to use AI to assist in filling in college entrance examination volunteers, but this year, with the blessing of large models and the reform of the new college entrance examination, it is difficult not to make the market full of interest.
The so-called new college entrance examination reform is to replace the original liberal arts and sciences with the “3+3” and “3+2+1” self-selected subject model. An obvious change is that this year, not only has the number of parallel volunteers increased to 45, but also up to 6 professional volunteers can be filled in in the professional group volunteers of each college, which directly leads to more complex college enrollment and volunteer filling policies.
The application guide, which is often more than 300 pages thick, also exposes candidates and parents to a greater risk of making wrong choices.
However, the essence of filling in the volunteer is still a set of screening and matching data: usually based on the college entrance examination scores, the part that is not below the threshold is screened from many universities and colleges across the country, and then the most suitable one or several items are matched according to the needs of candidates from this part as the first choice and alternative.
No matter how complex the data, systems and decisions involved, they are all professional counterparts for AI large models. Baidu, Quark, QQ Browser and other new and old players have also made “AI volunteering” the main project of the summer.
As a result, whether the level of AI volunteer filling with the blessing of large models is reliable has become a topic of endless debate. What are the characteristics of these AI filling tools, and who is more reliable? Will the help of artificial intelligence make it easier to apply?
To achieve these three challenges, product managers will only continue to appreciate
Good product managers are very scarce, and product managers who understand users, business, and data are still in demand when they go out of the Internet. On the contrary, if you only do simple communication, inefficient execution, and shallow thinking, I am afraid that you will not be able to go through the torrent of the next 3-5 years.
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In order to find the answer, we personally experienced the three most popular applications on the market, Baidu, Quark, and QQ Browser (Tencent), and evaluated the platform in the same environment and under the same conditions. In order to ensure the fairness of the test, the non-paid public versions of each AI are selected to see what kind of suggestions the AI can give in the case of “0 charge”.
01 Information enrichment becomes a basic requirement
Applying for volunteers is essentially an information war, and whoever receives more accurate information can seize the opportunity in the application.
In the past, candidates needed to query their volunteer forms, relying on a single channel of information was not only inefficient, but also possible to slip due to errors in information judgment. The AI volunteer filling product uses algorithms and big data to realize the scientific collection and integration of information, and intuitively presents multiple application plans to candidates. Therefore, the importance of accurate information is unquestionable.
First of all, let’s take a look at Quark, which has launched a college entrance examination channel to help candidates and parents screen. It is worth mentioning that Quark just launched the first college entrance examination volunteer model some time ago, and simultaneously launched three major functions: “college entrance examination in-depth search”, “volunteer report” and “intelligent selection of volunteers”, with a complete college entrance examination knowledge base.
The core function of “Volunteer Report” is an agent that runs in the form of an agent and can generate a complete volunteer plan.
In just 5 to 10 minutes, Quark will simulate the analysis path of volunteer experts, and design 15-20 pages of volunteer application plans with different gradients for candidates around multiple dimensions such as grade ranking, interest region, and future employment tendency, and generate a professional volunteer report.
We select the college entrance examination province here in Henan, the subject is physical and chemical science, the score is set at 555 points, the target college, regional preference, professional preference and other interests and preferences are not limited, and the supplementary information is filled in as “need good employment”.
Source: Quark College Entrance Examination
In the end, the results given by Quark are quite rich, giving the basic information of the candidates, the design of support filling strategies, the details of volunteer filling, the interpretation of the volunteer form, and the risk warning, and the overall content is detailed and has a high reference value.
Similarly, we enter the same conditions in the QQ browser to generate a college entrance examination volunteer report.
QQ Browser gives information in six sections, including candidate information, strategy description, volunteer form details, volunteer form analysis, key college interpretation, and risk warning.
Baidu launched a college entrance examination column this year, integrating common content related to college entrance examination volunteer filling, in addition to its own AI volunteer assistant, it has also launched AI chat volunteering and college entrance examination big data, but although there are many functions, it is basically result-oriented, lacking active analysis content, and users need to take the initiative to input, and the report generated by AI chat volunteer is a little thin compared to the report of Quark and QQ browser.
Source: Baidu College Entrance Examination Column
As for the in-depth analysis of college selection and other aspects, the three products actually continue last year’s strategy of “rushing, stabilizing, guaranteeing, and AI three axes”, from the perspective of the number of school recommendations, Quark gave 1,242, QQ browser 642, and Baidu 320.
In addition, if candidates feel that majors are more important, Quark also gives priority to majors.
Although there is a significant gap in quantity, each company has done a very comprehensive and detailed job at the data level, from the reportable professional group to the scores over the years to the enrollment plan, and even the tuition fees and subdivided subjects are given as a reference.
Source: Quark College Entrance Examination
It’s just that in the most important function of admission probability, the slightly different analysis results and calculation methods of each company, as well as the dazzling big data, even parents may be confused when they see it, let alone students who have just graduated from high school.
According to our inquiry based on the information given by various platforms, these contents come from authoritative official websites, admissions brochures, professional books, and famous teacher videos and other channels, and finally are sorted out and summarized by AI synthesizing the information of the whole network, and are output by various algorithms. It can basically be understood as simply filtering by data and then giving suggestions.
From the perspective of overall information richness, Quark and QQ browsers can actively give richer information, which is more friendly to candidates who do not have too clear ideas, while Baidu integrates more information content that needs to be passively obtained, which is suitable for candidates who have their own ideas.
In terms of core college recommendations, in addition to the difference in quantity, all three can meet the needs of candidates and parents.
Of course, volunteering is not a simple score matching, but an in-depth decision based on personal characteristics and career planning. Therefore, if you want to use AI to assist in filling in the volunteer more accurately, you can enter your thoughts and preferences in detail as much as possible to get a more accurate answer. This is also an important testing standard that reflects the level of AI.
02 Personalization takes it to a new level
Under the traditional volunteer filling model, candidates can often only refer to the admission line over the years based on the score segment, with a narrow range of choices and a lack of accurate analysis of personal interests and abilities, and it is easy to fall into the dilemma of “high scores and low scores” or “professional unsuitability”.
Relying on big data and algorithm models, AI filling tools can achieve multi-dimensional analysis from scores to personal characteristics, providing candidates with a variety of colleges and majors to choose from.
Therefore, we also conducted more in-depth customized testing on the three platforms.
First of all, quarks. As mentioned above, Quark supports filling in personal information files, including target institutions, geographical preferences, major preferences, priority strategies, graduation plans, career preferences, tuition preferences, and other personal hobbies, family backgrounds, and other information that can be filled in.
Source: Quark College Entrance Examination
This feature focuses on personalized scenarios. When candidates have a tendency or general direction for their choice, Quark can analyze from a variety of aspects and further assist in the application, just like a private customized volunteer application form, with a more comprehensive experience and recommendations that are more in line with the needs of candidates. For example, when some candidates want to choose a literature major and then tend to “take the public examination” in the future, they will generally struggle with whether to choose a good school or a good major. This kind of question without a standard answer is difficult for traditional search engines to answer, but with the help of AI and large models, relatively suitable suggestions can be found.
In addition, if the candidate has a lot of questions, Quark’s “college entrance examination in-depth search” function is useful. In order to improve the accuracy and professionalism of the answer, the real needs of the candidates will be refined and disassembled, and each type of demand corresponds to the customized answer paradigm and key points to ensure that the reply is both targeted and deep.
Then there is the QQ browser, its information collection link is not much different from quark, and it is also very user-friendly to give basic information templates, just check like a multiple-choice question, but there are 10 regional restrictions in regional selection, and up to 8 are supported professionally, and then search with this.
Source: QQ Browser AI College Entrance Examination
In addition, QQ Browser can also query basic information through dialogue. For example, query scores (query time and channels for college entrance examination results in different provinces, one-point curve chart, etc.); enrollment plans of different provinces and universities; Professional segmentation and employment situation are equivalent to having an exclusive college entrance examination consultant.
Baidu looks like a conversational AI Chat, but there are many differences when explored. For example, Baidu can create multiple volunteer forms, which avoids the trouble of changing information multiple times if there is a change in grades or multiple candidates at home.
Source: Baidu College Entrance Examination Column
Moreover, in Baidu’s AI chat volunteers, you can also view the results of multiple large models, including the results of general large models such as DeepSeek-R1, which is more referential.
Source: Baidu College Entrance Examination Column
In addition, when candidates are faced with multiple favorite colleges and majors and cannot decide the order of volunteering, Baidu has also launched a comparison function in the “Employment Prospects” section, which can make decisions more objectively.
Source: Baidu College Entrance Examination Column
In Baidu’s college entrance examination service, there is a “college entrance examination live broadcast room” section, where you can not only squat to watch the live broadcast of the college admissions office, but also enter the live broadcast room of seniors and sisters for real-time consultation, which is also a special function.
Source: Baidu College Entrance Examination Column
It is worth mentioning that according to the score line and the big data of previous years to assist volunteer decision-making, although rational and objective, it is easy to ignore the candidate’s own personality and interests. Therefore, this year’s product design of Quark, QQ Browser and Baidu can give some suggestions on professional application in terms of personality, and candidates can take a free MBTI test to adapt to the major according to their personality and get comprehensive advice.
In fact, in the process of in-depth use of these three AI volunteer filling platforms, it can be clearly felt that in addition to richer and more accurate content, this year’s products have been upgraded and iterated in every link from information query, plan formulation to data collation, in response to the diversified needs of candidates and parents. It effectively solves the pain point of traditional volunteer filling that relies on volunteer letters and a small number of consultation channels, and is difficult to meet complex needs, bringing convenience to candidates, but can AI volunteer filling really help candidates make decisions?
03 AI volunteer filling is only an auxiliary
First of all, it should be clear that although the AI volunteer filling tool shows strong information integration and recommendation capabilities with the help of large models and big data, its positioning is always only an auxiliary decision-making tool in essence.
It is like a “data brain”, which can quickly analyze a large amount of information, but in the end, what school to choose and what major to study also needs to be combined with the actual ideas and future plans of the candidates, and in the end, it is you who makes the decision.
Zhang Fan, head of Quark Search, also believes that AI and human college entrance examination volunteer experts are not a simple replacement relationship, but a complementary cooperative relationship. “AI can change the way volunteer experts work to a certain extent and improve the efficiency of volunteer reporting.”
In specific use, AI should also be used as an “information filter” rather than a “decision-making substitute”, and more evidence should be found to cross-verify information, rather than relying only on a single information source. For example, use AI to quickly screen college professional groups that meet the score range, narrow down the selection range, and then manually review the accuracy of the recommendation results, such as checking the latest admissions regulations on the official website, calling the college admissions office to confirm the subject selection requirements, and synthesizing multiple information to ensure the accuracy of decision-making.
It must be admitted that for most candidates, as long as they make good use of the capabilities of AI, they can indeed achieve twice the result with half the effort when filling in volunteers. Moreover, most of the AI volunteer filling functions launched by Quark, Baidu and QQ browsers are provided free of charge, and there is no need to pay membership fees or pay high tutoring fees, which can also narrow the gap with other candidates with superior conditions to a certain extent.
In general, the value of AI volunteer filling tools lies in using big data to lower the threshold for information collection and provide candidates with “rational reference based on probability”, but the core of volunteer filling is still “people’s planning and choice for their own future”. Only by combining the efficiency of AI with artificial insights can we find the optimal solution between scores, interests, and reality – after all, the choice of university majors and colleges is never just a simple matching of a set of data, but also a deep reflection on the direction of life.
Resources:
Quark College Entrance Examination, Baidu College Entrance Examination Column, QQ Browser AI College Entrance Examination Pass
