What's up everybody, Jayce here for JaspiesCaseBrace.com, 2021 P&E National Tragist Collegiate Football First off the line edition, one box break, random teams number two just sold out. And again guys We go by this checklist here on group break checklists just in case I'll drop it in the link in the chat as well But we go by this checklist here for the hits and again, it's a quick little one box break guys So good luck. Here we go. Dice really here. Here's the customer name So from Brandon and Brandon got the last two right here and then the winners there from Prism 27, Prism 28 are right there There's the teams all teams in all names roll it two and a five seven times good luck one Two three four Five six seven seven times two five seven Brandon down to Brandon. All right seven times One two three four five Six seven Seven times seven seven 40 riders out of the Patriots So Brandon with the 49ers Aaron, you have the Saints and Cardinals Brandon with the Jaguars as well as the Chargers and Chief Steve with the Bucks Yann with the Broncos Adam with the Giants Brandon with the Lions as well as the Vikings and Bills Jeff with the Ravens Sean with the Texans Brandon with the Eagles as well as the Cowboys Steve with the Falcons Adam with the Raiders Brandon with the Dolphins Jets and Panthers Jeff with the Commanders Aaron with the Steelers Timothy with the Browns Sean with the Seahawks Harry with the Bengals Jeff with the Titans and Packers Sean with the Colts Simon with the Rams Jeff with the Bears and Brandon with the Patriots So if any excuse me if any of you guys want to trade Give you guys a quick little trade window. If not stick to what you got. All right. I'm assuming driven the clothes on guys no trades Stick to what you got and then I got three boxes here guys one two three Let's see if I can roll one here one two for the top three four for the middle five six for the bottom And that doesn't work. It fell right to the bottom Actually, you know what? Let's just use a virtual one So there you go here we try this again can't believe that I spoke about all right here we go Rollets One so top box one two at the top. Yeah, that's why I don't play. I don't play at Vegas. I'm not a good dice roller All right Here we go top box Here we go First off the line. All right. Here we go guys First one is a four out of ten Clyde Edwards Lair She's gonna go to the Kent City Chiefs We have a D'Ami Brown to 75 Be Washington Commanders We have a Mac daddy Jones for the Patriots 25 out of 75 Let's say actually Mac Jones is still playing going into the second quarter. You know, that's Patriots First auto is the boss Five of ten Brian Bosworth. So I assume he's gonna be under the Seattle checklist I think you only ever played for Seattle and yes Seahawks Brian Bosworth five of ten Got a dual autograph that is Kylin Hill and Jake a KJ Costello That is number two ninety nine so Kylin Hill is Packers and then KJ Costello is none So that'll be Packers and none if Packers win the randomizer it'll go to the Packers if it's none everybody gets a shot at it You got a book It is Oklahoma State, Thailand Wallace 70 out of 92 and then Thailand Wallace I believe is a Raven all right. Yes Baltimore Ravens with that one. I have to put that in a little slider box here to the side How about my boys Devonte Smith very nice one out of eight RPA? That must be the first off the line exclusive Nice Devonte fly eagles fly who has the Eagles Who has my Eagles? Brandon there you go, buddy and last one here is a nine out of ten Jamar Chase Wow, look at that Chick-fil-A bowl patch right there. That is very sweet Go Tigers Have touched the patch beautiful patch right there That is pretty sweet since 90 bangles who has the bangles? Harry there you go Harry nine out of ten that is pretty sweet And we'll also have to put that in the slider box as well There you go guys, so that was a quick little box right there So let's do a quick little randomizer here and again. It was gonna be Packers and none dice roll roll it five and a five ten times one two three four five six seven eight nine 10 It's gonna go to the none spot which everybody's gonna have a shot at that so we use the same dice roll at 10 times Let's copy and paste the names 10 times one Actually, sorry, that was only 30 Let me copy everybody one two three four five six seven eight nine 10 so 10 times Brandon at the top and I don't even know if Brandon had the Packers, but Jeff did so there you go, man. So none spot got it and then Brandon at the top So I'll paste your name on there with that and there you go guys. That was a break jaspyscasebrace.com guys. Thanks


I thought we ran out of gas a little bit. We dug ourselves a hole. I thought the first half was the game. You know, the stats speak for themselves. We knew what they were going to do. And those three things were fast breaks, 27 points, second chance points, 33, and points off turnovers, 27. It was almost 90 points in those three areas that we came into the game trying to address. I didn't think we had the requisite physicality in the first half. Dug ourselves a hole. Came out and played a really good third quarter. But I think we ran out of gas. And they were exceptional shooting the ball tonight as well. But part of that is that you've got to match the physicality, take care of those details that we discussed in the morning. Was it bringing it to be? Was it knocking down the shots?  But I think there was too many opportunities for them in transition, or we weren't up to touch. We weren't receiving the shooters high enough. So plenty of mistakes in there. But we also did. They did make some more regarded at well. Two questions. Understanding, one, that there are, I think, 15 to 2 without job. But all of the things that you mentioned are things that you went over with. I'm sure you're well aware of. Considering where you are, and the standings of where you are in the season, I guess how disappointing is that? 4-1 and 4-1, but you still have a match that you could tell. Well, it is a new group. I think we're still learning each other. I think, if anything, it's a great experience for us. We learned that's how teams are going to beat us. This is the way they play. They're excellent at it. They're bigger and stronger in us at every position. So it is a challenge to match their physicality. But we've got to match and be prepared for it. It's a lesson. It's an opportunity for us to see what the playoffs are going to look like, and how we're going to have to compete. Can I ask you guys to chip away from this double digit lead at that point? I thought physicality. We were physical. We got the ball off the rebound and ran, and we were able to get to our spots earlier. Clear space earlier. I thought in the first half, we also didn't do a good job of that. We were jogging down the floor instead of running and getting them out. They're exceptional if you allow them to zone up. And in the first half, too often we did. Well, I mean, I really, we all know we want Kairi. We need Kairi, but I really don't have any comments until I see him out there. You guys obviously struggled with Kevin got hurt earlier in the season, and this team as well. 15 minutes from now. What do you think allowed them to win? It's a high-level team. It's one of their stars. They have to figure it out. Talent. You know, they have a talented, balanced roster. You know, our roster is built on three stars. When they're out, it makes it very difficult. It puts a big strain on guys playing roles that they haven't played before.


The United States Army presents The Big Picture, an official report produced for the armed forces and the American people. To most Americans, the very symbol of government is the capital building in Washington, where the machinery of democracy works its wonders. Almost in its shadow is another building which symbolizes just as strongly one of the indispensable freedoms in our democracy, the National Press Building. There is no accident of history that the American people are the best informed in the world. From the very beginning of the American experiment, it has been recognized that only with a free and unshackled press can democracy survive. This recognition of the press' importance has given it a position of undeniable privilege and prestige in our society. But it has also placed upon it the grave obligation to keep the people truly informed. Nowhere is this obligation more certainly recognized. Nowhere is the responsibility more keenly felt than in the National Press Building. Its distinguished tenants have behind them a breadth of knowledge of our national life exceeded by no other group. The knowledge of the intricacies of the American scene in all its locations. For these men comprise the Washington Bureau's of leading newspapers and news services throughout the country. And for their readers in all parts of the nation, they record day by day history as it is made at the seat of government. The tradition of irresponsible and professional press is heavy in this building where the proudest trophies are the press plates of memorable front pages. The men of the Washington Press Corps are among the finest their profession can produce. Most of them in their careers have chronicled the political contest, the social upheavals and the wars which have formed the story of our time. One of the most respected members of the Washington Press Club is its president, Mr. William Lawrence of the New York Times Washington Bureau. He is here shown introducing General Maxwell Detailer to the National Press Club on the occasion of General Taylor's retirement as Chief of Staff of the United States Army. Later with Mr. Lawrence we will screen the actual combat films of the middle phase of the Korean War. Bill Lawrence's daily job of reporting brings him into constant contact with the men and events who make headlines. He is exceptionally qualified in the field of newspaper reporting. In his 18 years with the New York Times, Bill Lawrence has covered some very significant stories. During World War II, he was for a while Chief of the Times Bureau in Moscow. Then he reported on the war from Okinawa. He flew with B-29s over Tokyo and other Japanese cities. And after World War II he covered the Civil War in Greece. And then with many other illustrious reporters, he saw and reported the war in Korea. Today we are fortunate to have Bill Lawrence with us to look into a particular phase of that war. Good to see you, Bill. Good to see you too. You know, I was very fortunate recently on a big picture to have one of your colleagues, Jim Lucas of Script Howard. Yeah, I got a chance to see that one, Stu. And as I remember, Jim picked up the war about the beginning in June and carried it up to the defense of the Puson Perimeter. That's right. And today I'd like to pick it up from that same point, carry it on. From that period when we broke out of the perimeter in September 1950. Seems like a long time ago, doesn't it? Well, in some ways it does. I've covered a couple of wars since then and found a lot of stories from a lot of different places. And yet, no one who was there, soldier or reporter, is likely to forget it. Especially that period you were just mentioning, September-October 1950. That was a period of pretty high morale, wasn't it? Oh, very high. You see, first there'd been the retreat and then that holding operation along the Nactong. And then finally, we were able to go on an offensive that... That was smashing the North Korean Army. That's right. Bill, you're the kind of a reporter that calls the shots as he sees them. Your record speaks for itself. A very accurate one. I have a book of clippings of stories that you filed during the Korean War. And I'd like to read a sentence from one of them. Shoot. You read it in late August 1950. There is a sense of optimism in American circles, but certainly could not have been detected two weeks ago. What prompted you to write that? Well, let's recap a little bit. Swiftly, treacherously without warning, the North Korean Army had smashed across the 38th parallel in late June. They fully expected they'd be able to drive all the way down the peninsula before anybody could or would come to the aid of the South Koreans. But fortunately, the United Nations were able to act swiftly. They branded this an act of regression and this authorized other nations to come to the aid of the South Korean Army. Now, the first available troops were those U.S. occupation forces stationed in Japan. Just three divisions. Badly equipped and under strength. And the North Koreans were strong and well-equipped. They'd prepared for this invasion for a long time. And consequently, our forces had a pretty rough time of it in those summer months of 1950. About the only thing we could do was withdraw to a defensive line south of the Naktan River. Well, withdraw is a polite way of saying we got chased there. And we did hope we could hold there while we'd build up supplies and equipment and men. We did manage to do that, although it seemed like a pretty thin hope very, very much the time. But it did break up the enemy's plan for a quick push all the way down the peninsula. Well, it just couldn't get through, as I said. Every time he tried, the enemy weakened himself a bit more. And at the same time, from America and from other nations, troops were pouring into Pusan more and more equipment. And we were rebuilding the South Korean Army, which had taken such a terrible beating in those early days of the war. And so, with the knowledge that we were going to make this play at Incheon, it was possible late in August to report truthfully that a new sense of confidence was taking hold. Looked as if things were really going to happen. It did indeed and things did happen. More swiftly and on a grander scale, anybody could have dreamed the day I wrote that story. On September 15, 1950, the U.N. forces take the offensive. An assault fleet appears off Walmy Island at Incheon Harbor, 150 miles behind enemy lines. It's a daring end-run maneuver which takes the sleeping enemy completely by surprise. At 0630 hours, the Marines begin the assault. The naval barrage has cleared the way for them, but this is still a risky operation. Headquarters must gamble on the first try being good. Incheon's violent 30-foot tides lead no time for a second attempt. We had orders to neutralize resistance and do it fast.  It took us 58 minutes to secure the island. With the next tide, more Marines move into the streets of Incheon itself. They meet little resistance and within hours the city is secure. The big gamble has paid off. With the surrender of Incheon's modern harbor, the back door to Seoul is open wide. Simultaneously in the south, the reinforced 8th Army breaks out of its Busan stronghold, splitting the encircling Red Forces as it thrusts across the Naktong River to begin its drive northward. At Incheon, the 7th Infantry Division swarms ashore to strengthen the UN foothold in the north. Thousands of enemy troops are being trapped in the southwest as the Busan spearhead races north to join up with Incheon forces. On the way to Seoul, we took a good many prisoners too, but they didn't come easily. United Nations strength is growing in the north. Men and machine, first hundreds, then thousands, blow inland from the sea to join the attack towards Seoul. With each step, however, they meet stiffening resistance as the retreating enemy consolidates his forces. At Busan, still another nation joins the growing UN command as 1,200 men of a crack Philippine regimental combat team come ashore. And at Kimpo Air Base south of Seoul, men of the 187th Airborne Regiment arrive from Japan to become the first paratroop unit to enter the conflict. This newly recaptured airfield has also become an advanced base for increased air attacks on the enemy's supply and escape routes. As the spearhead from Busan gathers momentum, columns of transport barrel northward against a disheartened enemy. In many towns, the entire populace turns out to shout its welcome. Like France all over again. Couldn't understand what these people were saying either. Some places, nobody was around to say anything. It's only about 20 miles from Incheon to Seoul, paved highway all the way. But it took us a week of hard fighting to make the trip. Finally though, our amphibious gear crammed full of rock and American marines started massing up at the Han River across from Seoul. It was time to retake the city. The softening up process got underway. Air crossing means a full-scale amphibious operation. Since the Han here near its mouth is well over a mile across. The Reds who had thrown back an earlier night attack were gone. Pulled out to dig in among the streets of Seoul itself. The battle for Seoul was rough. 10,000 communist troops garrisoned every building in street junction with orders to fight to the death. Great many did. City is retaken September 26th. During the battle for Seoul, the trap is closing swiftly about Red forces in the southwest. The day after Seoul falls, troops from the 7th and 1st Cavalry Divisions join up just south of Suwon. Two days later in the battered capital building, special ceremonies are held as General McArthur officially returns the city to Seng-Min-Ri, President of the Republic of Korea. It now begins a tragic homecoming for the thousands who had fled the city only three months before. You'd look at these people scratching through the ashes of what used to be their homes. Wonder where they got the guts to go on. Still, I guess we'd do the same back home if it came to that. As life begins to take root again in Seoul, the U.N. advance in the eastern sector goes on. On September 30th, rock forces reach the 38th parallel. They cross it the following day. One old guy couldn't keep it straight, who is who? Turn out to meet the rock army with North Korean flags. The end of September finds the war back where it started. But the cost has been great. On October 6th, at a U.N. cemetery between Seoul and Incheon, Major General O.P. Smith, 1st Marine Division Commander, honors Marine dead. Representing the army is Major General David Barr, 7th Division Commander. Three in-groups are honored by Colonel Park In-Yip, commanding the Rock 17th Regiment. The silent thanks and admiration of each commander for what his men have given is echoed by the people who hold their freedom to that willing sacrifice. Elsewhere, the conflict goes on without letter. The 29 squadron, based in Japan and on Okinawa, continue their daily blasting of red industrial and transport centers in the north. For us, it was a funny situation. The commuters were, somebody called it.  Funny situation. In the south, refugees are becoming a major problem. With thousands of red soldiers and guerrillas in civilian clothes trying to escape to the north, each refugee must be individually time-consumingly free. To the north, events are moving so rapidly that reinforcing units are hard-pressed to keep pace with the U.N. advance. On October 9th, Kesang is taken. This surrender frees the last South Korean city held by the Reds. Then on the east coast, Wonsan. Just two days after the fall of Kesang, Rock 3rd Division troops seize the port of Wonsan, having marched 287 miles in 20 days to get there. They met little resistance. Next, the Red Capital itself. On October 17th, men of the 1st Cavalry Division worked their way into the outskirts of Pyongyang. In less than 24 hours, the North Korean capital is in the United Nations hands. These were important victories. Incheon, Seoul, Pyongyang. Very important indeed. You know, complete victory seemed just around the corner. You know, as a matter of fact, if you don't mind, I'd like to quote a phrase you wrote right after the fall of Pyongyang. Now that the Korean War is evidently drawing to an end. Well, that does read a little silly now, doesn't it, considering what happened for the next three years. You can't remember that that was before the Chinese Communist hit us. And everybody, the highest military brass, the G.I. on the line, the reporters, all thought that the North Korean Army had been smashed so thoroughly that the mopping up process would take only a few weeks. Psychological warfare plays an important role at this stage of the fighting. Using high-powered speakers, Si War planes fly ahead of advancing U.N. troops, booming their message in Korean to the retreating enemy. Safe conduct passes prove highly effective. More than once, whole enemy companies lay down their weapons and wait for our troops to arrive. Two days after Pyongyang falls, our first combat airdrop in Korea gets underway in an attempt to cut off retreating Red Forces north of Pyongyang. As it inchs off, the Supreme Commander personally supervises the operation, nearly 2,000 troops making the jump. In a second wave, the heavy equipment arrives, air express. Local transportation is pressed into service. Next day, 1,800 reinforcements jump, but the enemy has already fled northward. In the east, rocked forces continue their headlong charge north from Wonsan to take Hongnam. Meantime, a Navy task force is waiting off Wonsan. 3,000 enemy mines had to be cleared from beach approaches before the Marine Force could come ashore. It was a delay, but we could afford it. The rocks had made us a welcome present, a beach with no enemy guns on it.  The mission now is to press this advantage. Continue the attack toward the Alu. Swiftly, the Marine Force moves in on red-held villages and towns, and just as swiftly, out the other side. Spirits are high. Three days later, and more than 100 miles closer to the Alu, the 7th Division makes its landing at Iwan. Ships of every description swarm into shallow water to disgorge 7,000 men and their machines. Their only opposition, the deep, loose sand of Iwan's beaches. This far north, winter comes early to Korea. Cold weather uniforms are welcome, as the Division moves out to rejoin the attack. To the west, Marines are advancing over ground frozen harder every day. News of their approach runs ahead of them, as village after village is liberated. North Koreans meet freely, and the Christians among them pray openly for the first time since 1945. The shattered communist forces are pulling back into the last corner of this peninsula they had set out to conquer. UN troops follow as fast as the tortuous terrain, and increasing cold will allow. In the eastern sector, it is difficult even to keep contact with the retreating enemy. In the central sector, however, prisoners taken during a strong red counterattack give warning of potential danger. Many of them wear the quilted uniform of communist China. Meantime, in the northern sea of Japan, winter is giving off-shore forces a taste of things to come. Even routine supply operations are becoming a nightmare of icy wind and pitching decks. We kept our aircraft warmed and ready to take off the minute the weather lifted. Meantime, the Reds would have a lot less trouble moving troops and supplies on Korean roads. We didn't like that thought much. On the shore, the Chinese forces have pulled back, leaving a clear road to the Yalu. The village of Haishanjin huddles against the banks of the Yalu across from Manchuria. Here, men of the 7th Division set up their outposts. It seems a sorry spot to spend Thanksgiving eve. But from bases in the south, cargo planes are already taking off, setting courses northward across the frozen mile. They carry crates rigged for airdrop and labeled perishable rush. Turkey and the trimmings, courtesy of the U.S. Air Force. All over Korea, mass kits overflow with steaming potatoes, giblet gravy, cranberry sauce, the works. Along the Yalu, everything is quiet. Every man, no matter what his duty for the day, shares in the traditional feast of gratitude. Headquarters feel certain that one more U.N. offensive will end the fighting in Korea. Actually, a whole new war is ready to begin. Across the Yalu, the decision has been made. Full-scale Chinese intervention is about to bring the second phase of the Korean conflict to an end. And that threat of Chinese intervention, no one foresaw back at the time of the fall of the Yangyang. Well, the point is that it had been pretty well discounted by then. I think many of us, most of us, felt that the Chinese would hit us when we came in in Cheon, or never. And I remember the briefing going up on the troop ship, was that this was either the last inning in the ballgame or the first inning of a double header. Bill, I'd like to read from one other story you filed in Korea. Wars are so big and so violent, and move so quickly, that the individuals on the team often become necessarily anonymous. Almost faceless. Well, then you went on in this story and in others to give dozens of those faceless men a voice to describe their jobs and their attitudes to report what they were thinking and even what they were hoping. Well, that's right. I think it's an important job of war reporting to chronicle the attitude of the individual. It may even be more important than writing about the amount of ground that was won or lost on a given day. Wars have become so big that the headlines usually can reflect only what the team as a whole did. But behind every success, every defeat, there are dozens, hundreds, perhaps thousands of men whose individual attitudes have everything in the world to do with shaping that particular success or that particular defeat. Now, these victories we've been talking about today were terribly important in their day. And they were achieved simply because a lot of individuals did their job bravely and conscientiously. It's always been that way. Do you think that could be true today? Of course. No reason why it shouldn't be as true today as it was in Korea or in World War II or the American Revolution to that matter. Oh, I must admit that's one war I didn't cover. Our weapons have changed, but I've yet to hear of a weapon that fires itself. And so the individual soldier, or sailor, or airman remains the single indispensable factor of war. Bill Lawrence, thanks very much for being with us today. Now, this is Sergeant Stuart Queen, your host for The Big Picture. Inviting you to watch for our next episode in The Big Picture, which will deal with the last chapter of the Korean War. And we'll have as our guests the noted military critic and author, Brigadier General S.L.A. Marshall. The Big Picture is an official report for the armed forces and the American people. Produced by the Army Pictorial Center. Presented by the Department of the Army in cooperation with this station.


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Our next speaker, we have brought all the way from Melbourne in Australia. Professor Dragan Gasevich, he's a professor of learning analytics now in Monash University. He's widely considered the world's most foremost authority in learning analytics, with which his name is synonymous. He's the founding program co-chair of international learning analytics and knowledge, the LAK conference. And he's the founding editor of the Journal of Learning Analytics. So he comes with huge experience and I'm really looking forward to hearing what he has to say. Alright, thanks very much for the interaction and kind invitation, my pleasure to be here and also very pleased to see that so many people in higher education are so interested in learning analytics, so my trip was already worth it, so thanks very much for having me today. So I'm going to talk about learning analytics today and my key message is really kind of completely contained in the title as well that I have for today's talk. That learning analytics in higher education is about embracing complexity, rather thinking about learning analytics as a simple silver bullet or a quick fix that will solve our problems. I think that's really very essential. So before I actually start developing my whole argument and start sharing a fair bit of experience in terms of learning analytics, in terms of adoption in higher education, I'm going to just kind of quickly talk about some of the recent trends in learning analytics. In early days of learning analytics and why many institutions in higher education were so very much attracted to learning analytics is because they saw also clear value proposition in terms of both monetary but also student support. In many cases institutions were primarily attracted in the first place with some of these I call them deficit models, meaning identification of students at risk and trying to improve retention of students. Lots of important work was done in mid-2000s, 2007, 2011 at Purdue University. They developed and piloted a big system called the core signals and they showed considerable benefits in in terms of student success, in terms of student retention. However, over the time we actually start developing other types of learning analytics and start focusing more about optimizing learning, about predicting and describing different types of learning outcomes and learning processes. We also started talking much more about 21st century skills and something that makes our learners successful both workers and citizens in the 21st century and also thinking more about dispositions that our learners need to have. We are also able now to understand with the use of learning analytics much better what type of learning strategies our learners are actually taking when they are studying in different blended or fully online environments. And we are also able and that's I think I would consider one of the biggest successes of learning analytics. We are able to provide personalized feedback at scale where each and one of our learners are receiving a personalized message while our teaching staff are really not getting much increase their workload and students are getting much happier with that. Moreover, they are getting much better grades in many different contexts that we are getting to see. And of course we are also seeing much more progress in terms of frameworks for ethical use of learning analytics with privacy protection. All these things are great and many institutions are quite excited but this is the slide I've been using for the last five or six years and hasn't changed much. Most of these issues are still in early stages and they would tell you well we are still in early days of learning analytics adoption. Well we did this small pilot and we are still thinking about how to implement an rural learning analytics on a bigger scale. So what are those critical adoption challenges? We studied those in different contexts initially in the period 2014 and 15 with a colleague from Australia Shane Dawson and a big team of other Australian colleagues. I had a pleasure to work on their project which is funded by the Australian Government's Office for Learning and Teaching which benchmarked the entire sector in terms of higher education and analytics adoption. We just wrapped up another European project in September this year which was between 2016 and 2018. It was called SHILA. It was part of Erasmus Plus in which we both tried to benchmark the current state of learning analytics adoption and implementation in Europe and also develop a framework that will help higher education institutions to develop their policies and strategies for adoption. So we spent a lot of time discussing that framework but before that we're going to talk about some of these critical challenges that many institutions are experiencing in terms of adoption of learning analytics. First one is really the shortage of leadership for successful adoption of learning analytics. Many higher education senior managers are quite eager to have implementation of learning analytics yet they don't in many cases have sufficient backgrounds or clear understanding what are those clear benefits that learning analytics can bring and data science can also introduce in terms of understanding student success or other priorities for many institutions. More importantly where we are seeing even a bigger challenge in terms of leadership is academic leadership. Many institutions may have different professional teams that are quite equipped to deal with large amounts of data however in many cases they are not really clear in terms of what is that academic vision and what are the academic needs of their teaching staff and students. And then brings me to this next point. Two critical groups are barely at least in the literature ever consulted in terms of the implementation of learning analytics. That situation slightly changed since the systematic literature review we did in 2016 but yet in many cases institutions would be just going ahead buying a product without consulting two case stakeholder groups and their input was not sufficiently so in terms of the development of institutional strategies and policies. And of course critical point is related to lots of policy related dilemmas for many institutions. What about informed consent? What about GDPR? How we are tackling data protection of our students? What about security of our data? Institutions are not quite clear and this is fairly uncharted territory for many institutions and they are of course risk at worst because many things may also go wrong and they don't want to really kind of ruin their experience of their students but rather they want to be on the safe side. So considering these challenges then what can we do? What can we do better? And I'm going to spend most of my talk today on directions and the things that we need to consider in terms of development of learning analytics strategies and policies in higher education. In many cases what we actually saw in learning analytics is that institutions would start actually looking into fairly technical issues related to learning analytics. Those technical issues would be like what kind of data do we have? Or do we have data about students' logins to our learning management systems such as Moodle, Blackboard or Canvas or whatever other elements you may be using? Under these cases also they will be saying what other socioeconomic, demographic or academic data we may have about our learners? Can these data be joined? And if these two data sets can be joined can we also feed that back to some of these key stakeholders? Create a student dashboard or create a teaching dashboard or create a senior management dashboard? Those would be the types of conversations in most of institutions. Lots of things that are related to data crunching and data management as well. But in many cases we are seeing complete absence of consideration of different stakeholders who may have completely different concerns, privacy protection, personalization, adaptivity, data governance, interoperability and sharing of data with different relevant partners. How we incorporate these different stakeholders? There was the precise of the approach we took inside of the SHILA project in which we tried to develop a framework that can help institutions integrate the voices of the relevant stakeholders as they are going forward in the implementation of learning analytics strategy and policy. So inside of that project what we actually start from we actually start from an existing approach which was precisely developed to help translate evidence and scientific evidence into a policy. The approach is called rapid outcome mapping approach and then again this rapid is another abbreviation we can go indefinitely with different abbreviations with this particular approach. But a key point in this particular case is that we need to initially start from the understanding of the political context in which certain policy or strategy needs to be developed. If you are in Ireland you are clearly governed by different higher education rules in comparison to any other European country or in comparison to Australia. Therefore you may have a completely different political context. Also each institution has a different mission serves a different slightly different segment of the population of the students in spite of being in a country which is not perhaps huge in terms of student numbers yet some institutions are quite urban others are more rural others are institutions are also serving some more privileged students others are actually serving lower socioeconomic students. It is very important to recognize that political context. Another critical thing is also to identify early enough who are the relevant stakeholders and think about the relevant stakeholders. The third point is to define the purpose of learning analytics or what kind of behavioral change we want to see with learning analytics is that retention is that for example improved learning design or the overall experience of our students or as priority you have nationally here is the student success. Then what kind of engagement strategy we think if we want to enact our initial objectives once we have mapped out the political context in the agency stakeholders and define the purposes. Then we also need to pay attention and bear in mind what is our institutional capacity to have the capacity to tackle some of these critical issues and the final thing is also we need to have a framework based on which we can see what is the success and monitor success of our initiatives and more importantly also to build organizational learning memory. So based on the experience that we are getting from learning analytics and the evidence produced we can get the our institutions to learn from some of that implementation but we didn't really just start and use this particular framework in our work rather we actually developed a methodology which engaged a wide range of relevant stakeholders we engage students more than about 3,500 students across six different European countries also a smaller sample from Ireland as well. Students were first of all involved into focus groups to understand their qualitative impressions and expectations from learning analytics but also to understand their challenges and moreover we also developed a psychometric instrument which measures students expectations from learning analytics both in terms of ethics and privacy and particular services that may be expected. Surveys fairly succinct only 12 items and is also measuring ideal and predicted or realistic expectations of our students so we can see what students really want and what they think that they would get from the institution if they are actually going to get some of these services. Similar approach was followed for academic staff we then also interviewed more than 70 different senior managers across Europe that are in leading roles and they were responsible for sponsoring different learning analytics projects plus also we worked with European University Association and administered the survey which helped us to understand the readiness of higher education institutions. We also followed and discussed with experts by conducting an exercise which is called group concept mapping but asking what are those high priorities for learning analytics policy and strategy in any higher education institution. Finally we engaged many stakeholders through numerous workshops organizational or national level different types of events and also consulted with many different national agencies such as for example Quality Assurance Agency in the UK, JISC in the UK, SERF in the Netherlands and several relevant organizations Spain and Estonia. What we did as an outcome of this is created the Sheila framework and also four institutional policies that follow this process as we were actually going forward. So what I'm going to talk about today is I'm going to talk about this final product. It's a nice shape image that we developed as a result of three years work but this nice shape six angles image is actually representing that learning analytics policy is really considering six critical dimensions. The same six steps that we discussed for the Roma framework except that we are not suggesting that these dimensions are implemented in any particular order. Clearly identification and mapping out the political context is the clear first step but in many cases that also requires involvement of the relevant stakeholders as institutions are going forward and similarly also thinking about what are those critical purposes of learning analytics as they are going forward. More importantly what is at the core of the Sheila framework is the three elements. As you can see those are the action points that we documented. We also documented the relevant policy questions that institutions may have and finally we also documented a number of challenges that other institutions experienced as we were engaging with them. Final result and you can download it immediately it's just the Sheila project.tu slash Sheila dash framework is available and you can actually consult it but it's also offering a wide range of different experiences action points challenges that other institutions didn't or did consider and it's also something that will help other higher education institutions as they are going forward in the implementation of learning analytics policy. I'm going to now dive into these dimensions and think and basically try to engage us into the conversation about thinking what we mean by some of these critical points of learning analytics implementation. In terms of mapping of the political context we typically really see major drivers for learning analytics. Some of them are internal for example we see many institutions they are trying to promote learning and teaching excellence. In some other cases these are kind of between internal and external because government policies are for example pressuring institutions to pay attention to student retention. However there are other relevant external pressures that institutions are also experiencing as their drivers for learning analytics. In the UK that's teaching excellence framework as you can imagine or when I was previously with the University of Edinburgh they were also trying to understand why the university was receiving particular scores from students through national student survey. So they were trying to optimize their overall student experience in spite of the institution not having any problems with student retention. But some institutions are also feeling lots of pressure that they need to just jump on board with learning analytics because they are actually in fear of being kind of left alone. But in many cases they are really kind of experiencing many of these resellers I wish to say of learning analytics products. They are actually trying to sell them artificial intelligence without really much understanding what are the issues in higher education. What are tangible problems. They are just kind of trying to sell them uninformed type of myths that you know deep learning or neural networks can do the magic. And then you know we don't know what questions you may have but then you will get plenty of answers and then you go figure what questions you may have. And this is really a reality like a couple of years ago when I was still in University of Edinburgh I was always talking about these things as fiction stories but then we are receiving a call and our senior vice principal is asking me to talk to that company. They are selling us this product for student retention. I'm responding well we are not interested. We don't really have any problems with student retention. I ask them okay so what else can you offer with your product. Neural networks. That was it. And it was pretty much I had the conversation which was this cartoon. So the rest of the story is pretty clear. So be quite aware of these type of organic questions. So engage first with the types of questions and what are those critical points that you want to have in terms of learning analytics before engaging into any particular technological solutions. And then look for the technological solutions that are very critical for your understanding and addressing the priorities for the institution. In terms of the key stakeholders this is really some of the critical issues. Senior management is essential if you want to have a success. In learning analytics projects in higher education. Without sponsorship of senior managers it is really hard to bring relevant professional groups on board. IT, business intelligence, student services, other relevant organizational units that are important there. However in some cases even just having one senior manager sometimes is not really quite relevant. I was actually reviewing one of the leading Australian universities and their learning analytics initiative after three or four years. And all I basically saw was there are plenty of war stories. They basically had a learning analytics team which was reporting to the learning and teaching portfolio deputy vice chancellor. But then they had the IT team who were reporting to chief operating officer and then business intelligence team who were reporting directly to provost. Business intelligence team was owning the data. Learning analytics team was trying to get that data, wouldn't let them to access these data because they actually had completely different cultures in terms of understanding how you're addressing data. The learning analytics team had this kind of more data science approach. Give us data, data will tell us the magic. Business intelligence team had much different approach more in forward with the methods. What are the questions? And they could never agree upon on that. And the IT team was almost kind of found in between the two. So this is really very important to understand who are those relevant senior managers who can actually help us bring relevant professional groups on board and what kind of governance is needed for learning analytics. Students' perspective. We cannot emphasize enough how students find very important that their privacy is protected. That's the top consistent across all the different countries. And also they want to make sure that their data are ethically used. Some students are for example concerned that if we are trying to profile our students, if they end up in a wrong profile, that may also bias the grades that they are eventually receiving on different types of assessments for a good reason. And we need to have these get-kill guidelines. But then on the other hand, it's also important to engage with students to understand what are those legitimate interests as we are requested to have to deal with data according to GDPR. And what are those legitimate interests? The Sheila survey instrument is also providing us access to understand some of these legitimate interests. For example, we can see that there are cross-cultural differences across different countries. For example, why the UK students and the Dutch students completely agree about the importance of higher education institutions preserving their privacy and having ethical use of data. English students really just want to use also to see their data being used for particular services while Dutch students are much more careful about that. They don't want to do that. And so even if the institution may think that they have a legitimate interest to analyze data, if students disagree, then informed consent in such situations need to be directly obtained for particular purposes of learning analytics rather than to use a blanket approach for learning analytics. In some other contexts that as well might be completely fine as long as the relevant stakeholders agreed on that. Similar perspective is also shared by the teaching staff. There are in many cases even more concern about students' privacy and ethics than students themselves. That's well documented only in our research but also some of the research that was done even by the National Student Union in the UK. But then academic staff are by far the most concerned about their workload. When we send them the survey and we had also these open and questions almost every item received workload, workload, workload, workload. And the impression was that learning analytics will actually expect from all of them to become data scientists rather than analytics made streamline lots of these data collection analysis measurement and reporting processes and then also help them to make these better decisions. This also brings us to another important point that we need to convey these messages about what learning analytics can do for our teaching staff and also what are their workload implications and also what are these success stories that they can actually benefit if they engage with learning analytics. Experts, very clear. First thing that you need to address is ethics and privacy and the purpose of learning analytics and then you are good to go with other issues with respect to learning analytics. Those are the key I would say enablers for learning analytics. Of course according to the experts these are the issues that are easy to address because they are already existing frameworks that are in place and we collected a fair bit of actually experience in that. In 2016 Hendrick Drachler and Drachler also got the best paper award at the law conference by proposing the delicate checklist for institutions to help them to develop ethical and privacy protective use of learning analytics. So in terms of purposes of learning analytics that's something really that is very specific for every institution. But then once you have identified these purposes for learning analytics and those could be in some cases improvement of quality of learning experience dealing with scale in some institutions or improvement of personalized feedback in some other institutions or for example efficiency of some other institutions. In many cases we really need to think what are those implications for our primary stakeholders. So for example if you are running a student attention program in your institution identification of students at risk is only one small point that you will have to do. You will have to develop then a program that will engage these students and offer them additional counseling or academic opportunities that can actually help them to overcome some of the issues that are potentially identified as the risk factors. In other cases institutions are really just when you suggest analytics they are saying oh yeah we are developing a dashboard. That's almost like by default which is fine in some cases and I did also fair bit of share in developing dashboards as well. In many cases really very helpful for teaching staff and also senior decision makers inside of institutions. But what we've seen so far in terms of student dashboards they are mostly harmful if they are not done well. In particular what I'm referring to is comparison of a student with respect to the class average. There are many different studies that are suggesting that but when I just mentioned one a randomized controlled trial at Stanford University published earlier this year proper randomized controlled trial. They developed a dashboard which collected historic data decades of historic data about students grade distributions self-reported measures of the time they spent working in particular units that they were working inside of their university while they were pursuing their degrees and a few other things. Students were then randomized into two different groups one which was strongly encouraged to use the dashboard and the other one that was just informed about the presence of the dashboard. The group who was encouraged had a negative effect on their GPA through the engagement of this dashboard. So this is something we need to be very careful. Dashboards are not the only way how we can make effective implementations of learning analytics and that's really very important to consider. In terms of strategy and the engagement strategy this is really one of the key things that we need to consider in terms of learning analytics strategy and policy. It has to be well aligned with other relevant institutional strategies and policies. So typically most of institutions have their learning and teaching strategies. Many students are also having digital learning strategy or they are developing but they also have a number of other relevant strategies and policies in terms of IT data protection policy or data security policies that are quite relevant and also policies related to data management. Some of these things need to be very carefully considered and when you are creating these governance teams or steering groups that are responsible for learning analytics you need to bring them on board. I already mentioned the problem of the three different reporting lines in the Australian University but I also mentioned another similar issue that we experienced in Canada when I was at one of Canadian universities still I spent Canada for 10 years. So vice president academic had an idea to promote education innovation projects and we had one of these projects which was related to learning analytics which was heavily supported by the vice president's academic office. But then everything really worked well until the point we wanted to deploy particular technology onto the operational LMS of the institution. At that point the IT team told us that's against our policy and so they were pretty much telling like the chief academic officer who cares this is our policy and you can do much here. And then it took us more than six or seven months to get to the point that we were actually able to do even a small pilot against or together with the IT team. So this is something which is a real world and needs to be considered very carefully as we are implementing learning analytics. The other thing is also how is responsible and how some of these things are triggered. Some of these things are potentially triggered automatically but then the academic staff member needs to take the load. For example we are developing a technology which allows for personalized feedback provisioning for students. And this personalized feedback provisioning really requires input of the academic staff. But the approach works in such a way that academic staff member really needs to spend amount of time that is equivalent as if they are supporting three or four maybe five students depends on the complexity of the tasks students are using to provide personalized feedback at scale for hundreds in some cases thousands of students. However you need to account for the development of some of these rules as they are developing personalized feedback as well as bring the relevant expertise on board who can assist the staff members who perhaps don't have sufficient technical expertise to understand the types of data as well as to create some of these templates as you are implementing in particular cases. On the other hand the payback is quite significant and also as you are going forward you really don't have to repeat this exercise as long as students are following a similar learning and course design. This is another then critical thing to consider. Analytics really needs to and the policy needs to go to the core of understanding of the capacity, institutional capacity. The case that I mentioned from Australia that they were struggling with data was also that the institution really didn't have data lake meaning that they didn't really use APIs to allow different relevant professional groups and easy access to data but rather there was one data guardian who was protecting their institutional data enterprise data warehouse and this is one critical challenge. However in other cases as well it is important to consider what is the disposal strategy of the institution. Do you really have data and in many cases really collecting huge amounts of data is quite it could be expensive depends what kind of policy you actually have for that. Data storage if you are using cloud solutions are fairly inexpensive but then it's really important to understand what is that capacity and then have you also resolved issues related to data integration? Do you have sufficient unique IDs that are easily connecting relevant data paths that you may have across your campus and also get involved for example at the University of Edinburgh we had to involve chief security data officer who was responsible for also signing off some of the relevant issues related to learning analytics. Human I would say capacity is really really important. I can't emphasize it enough. Academic leadership is so scarce at this stage. We need to build much more of that human capacity. Many institutions are also witnessed a case in which they had this really strong professional group who was responsible for learning analytics but they felt completely disempowered to go to talk to academic staff and their perception was that academic staff could not care less about any of these changes to happen. Simply because in many cases they didn't have enough academic credibility to talk to the relevant groups who could actually accept some of the really good benefits of the technologies that they were producing and of course thinking about the infrastructural capacity. Final thing in my view is probably the biggest thing in terms of the analysis of the institutional capacity culture. Do we really trust data? Do we have the culture of even making decisions based on data? 2012 good colleagues Shane Dawson and Leah McFadgen they published about a Canadian university in which they were talking about a case study where institution was making decisions about their next learning management system that is they were reviewing the existing LMS and they were thinking what to do next and they were basically documenting how institution instead of make decision based on or by being informed with data institution made decision in spite what data were suggesting so this is really one of these critical things that we need to consider what kind of change management as well we have and how can we also have all our relevant stakeholders to be actually involved into that institutional change as we are actually thinking about the culture of the use of data and higher education. Final dimension of the Sheila framework is really talking about establishing monitoring frameworks. I'm afraid there are not many frameworks there and this is really not a big surprise I guess for many of you as well because the field of learning analytics is pretty mature and we are seeing anyways if you are not seeing many systemic adoptions of learning analytics across the world and how can you expect also to see many frameworks as well that are actually telling us what is important to think about but this is also something that we need to think about and some good examples are suggesting that we really need to think about relevant indicators what are those quantitative indicators in some cases that's easy that's pretty much like the number of students you retain versus when you didn't have the learning analytics implementation but also qualitative indicators as well is it the satisfaction of the students with their overall learning experience is it also qualitative really kind of improvements of the access to relevant services that students may have and enhancing that whole journey that students may have inside of the institution this is really very important to consider as we are talking about students in some cases as well relevant is to consider satisfaction but this is another critical thing to bear in mind with learning analytics in many cases it's really hard to isolate that tiny effect that learning analytics may be making why because all of your institutions are making so many different projects and developing different projects for example for student success without learning analytics digital learning strategy lms different platforms with your lecture capture all sorts of things and an analytics so the question is do you really want to anyways think about this kind of big whole thing or you want to try to think about one isolated effect in some cases you really don't care so much about the one single isolated effect unless you really are completely into the efficiency and optimizing all the use of resources in that case then there are methods that are out there that are helping us to think about the causal effects that can be derived from the implementation of learning analytics few more things and I'm gonna stop talking just quick epilogue of the use of the framework in terms of its practical implementation at one of higher education institutions in in Europe while I was still at the University of Edinburgh we developed learning analytics policy and now it's the whole strategy building developed so we did we decided on the advice of one of the vice principles digital learning to have policy developed in two steps first step was to develop something that can be used also as a vehicle to consult everybody on campus to kind of make a fuss but on the other hand also prepare a really simple two page document that is outlined the key principles and key purposes for implementation of learning analytics among these principles what we actually recognize the first one is that lots of data is out there available but in many cases they are just eventually used to provide models of reality and we know that whenever we are modeling models are reducing that reality does the data and the models are always incomplete and to make any major decision about our students we really have to have a human in the loop you can't simply set an email to some students we don't think you are going to make it that's as simple as that right another critical thing is and that's quite obvious transparency needs to be present there so by having these principles and purposes you are already becoming quite transparent and you are writing these principles and purposes in very plain English language rather than to use very kind of bureaucratic technical terminology that is very common for many policies that's another critical thing that of course you need to have good governance the University of Edinburgh decide to have that governance by establishing the governance group for learning analytics who would be vetting all the relevant projects that are going to emerge inside of University for learning analytics both in terms of the types of data they are considering in terms of the ethics and also how they are aligned with the purposes that are strategically identified for the institution and if they were not aligned and there was a dialogue why you are actually doing something that is not necessarily the priority of the University another critical thing that was identified in the principles is that institution shall avoid deficit models meaning we should not be just investing into the students who are struggling but equally so we need to invest into the students who are at the top of our ranking scales they need to be additionally challenged they deserve also equal opportunities themselves in many cases we also recognize that algorithms can perpetuate bias as mentioned also by the minister we had this quick conversation this morning and there was a colleague at TU Einhoven in the Netherlands who run a study by trying to really see what would happen if a predictive model for enrollment of students into an IT program would be also used as a decision maker for involving students first of all the most predictive variable emerging that process was gender of the students we unfortunately don't have many women in computer science information technologies however that gender for women would be a risk factor according to the predictive algorithm and what happened is basically if that algorithm was making these decisions over the course of several years you would have fewer women than more and that's really something we need to acknowledge that algorithms can be fairly dangerous and that's part of this principle for learning analytics at the University of Edinburgh final thing was a concession made to academic staff and the unions that learning analytics shall not be used for academic staff performance assessment as simple as that of course there was no unanimous consensus around the campus some were very unhappy they thought that was not really sufficiently strong to protect academic staff others were thinking they are actually not able to do their job with this principle but it's a really critical thing to consider in terms of purposes of learning analytics these are really something that is very specific for every institution you think the University of Edinburgh is thinking about the quality of their designs and the ways how experience of students can be improved also equity issues analytics is seen to measure different effects of particular initiatives that are trying to reduce or completely eliminate bias University of Edinburgh is particularly focused on the scalability of their online students fully online and they have a strategic priority and they were also quite concerned with the personalized feedback of students not that they are actually concerned with their national student survey ranking as well but it's completely directly caused by it also they were interested with students overall experience skills and efficiency but those are just some of the details that are relevant for a particular institution and as you are actually going to implement learning analytics in your institution you need to really think about what are your priorities that is to say purposes of learning analytics some of our war stories about the implementation learning analytics at the University of Edinburgh are documented by my partner in crime Anne-Marie Scott at the University of Edinburgh and that blog is also available so you are welcome to explore it and see what happened all right before I wrap up a few really quick final remarks learning analytics is not a quick fix but we really need to acknowledge and embrace the complexity of what we have in higher education we also need to recognize the critical role of leadership for the adoption of learning analytics both senior management and also academic leadership without those two we cannot really have effective adoption of learning analytics but in my view the biggest challenge is and we all need to work on that very hard is the development of data-informed decision-making culture that's not something we are really good at and so on that note I'm going to stop my talk and just basically one final plug for many of the institutions who are interested in higher education adoption we develop a MOOC which can help basically share plenty of these experience my talk is a really just a small summary of the things but the MOOC will be launched in late November so you are welcome to check out it'll be available in edX and everything will be also available under creative commons cc by licensed thanks very much for your attention wonderful it was well worth bringing you over from Australia absolutely


The 7 star cinderace terror raid event is back again this coming weekend. We're going to cover the best builds for you to go into this terror raid and beat it solo by yourself to make this easy for farming or even getting that cinderace if you've already missed this event. But before we get into today's video, please subscribe to the channel. Remember you can always unsubscribe later if you would like to. So from the 13th of January this coming Friday, we are going to see the return of this 7 star terror event. We've already had it once before, so we have a bunch of information going into it. That's going to make it a lot easier for you to take on this raid solo and even online if you would like to with these upcoming builds. We will of course do an update video as the event goes live to make sure you're aware of all the details like we did last time, but it is pretty much going to be exactly the same as it was the first time round. Remember if you've already caught the cinderace in your games, then you're not going to be able to catch it the second time round when this event returns. You can only have one cinderace from these events per save file. But if you did miss the events, of course, this is a great opportunity for you to jump back in and grab this exclusive event Pokemon with that special mark while you've got the chance to and also it's one of the best events that we're getting in the minute where you can farm a lot of really high cost items that definitely makes doing these events worthwhile. So we've already covered a couple of really strong builds options that you can take into this event then when it does come back around. But today I'm going to give you the three best builds. These are the builds I feel like they're the only ones you're going to need going into this event then. Slowbrow is the main option that you're going to go in against, but we do have a build for armor Rouge and espathra, which we've not actually covered on the channel before. But I think between these three builds, you if you use any of them going into these cinderace terrarium events solo in your game, you're going to be able to do them very easily, making farming them for the items an extremely easy task. So you can use these items to sell if you want to get a lot of money or just acquire a lot of Excel candies and things like ability patches, which are super useful for training Pokemon up in your games. Now the first build of course is a slowbrow. We covered this on the channel before. Let me move my camera down so I can properly show you all the details for it. But this is my preferred build. The Terra type is going to be psychic. It would make more sense going up against a fighting type cinderace. Going to have the life up item on there, not mandatory. Go for something like leftovers if you prefer the recovery, but I prefer the sheer power, the power stack that you're getting with that life bulb. You're getting a 30% damage increase with this item, although you do have the kind of setback of having that recall damage from any time you do attack the opposing cinderace. It is going to be level 100. Make sure if you're going into a seven star raid that your Pokemon is at level 100. It is important to do that. These Pokemon are all hyper trained as well. So using bottle caps to make sure that you've got 31 IVs across the board. Obviously if you are doing something like these Pokemon in particular that are all special attackers, then the attack stat is irrelevant. You don't need to train that attack stat, but everything else is quite important. The EV spread on this particular slowbrow is 252 HP and 252 special attack EVs with four of the remaining EVs put into defense. Now you can go a little bit more optimal with this EV spread. If you would like, I've done this EV spread in particular because I will be using this for other terror raids, not just the cinderace. But if you want to have a bit more of an optimal EV spread for this particular seven star raid, you can go 252 defense EVs and then 252 special attack EVs. It'll just mean you're taking a little bit less damage from those physical attacks that the cinderace is throwing out. Although really doesn't matter because you're going to be primarily using iron defense, which boosts your defense stat by two stages every time you use it. So the move set, as you can see, is psychic terrain, iron defense, nasty plot and stored power. I think after testing this a bunch of times with slack off, which is really useful for recovery, I don't feel like you need it. And you can set up a complete one shot with the life orb stack with the psychic terrain and then a combination of using iron defense, which is what you would start the battle off with.  Of course, you will see the cinderace from time to time. It will nullify all of the stat changes and abilities on your side of the field. So completely wiping out all of your stat boosts, which can be annoying. And that is something that's going to happen. It is completely random in these dens and it is going to be something that does happen from time to time.  And overall, this is probably the more consistent build of all of them. You can cut down the number of stat boosts that you take on your slowbro through a battle as well to make sure that you get some big damage off before those stats are nullified. Like you can do three iron defense boosts, two nasty plot and psychic terrain. And most of the time you're going to be able to get that stored power off and just chunk the cinderace and do a lot of damage. The ability on the slowbro doesn't matter too much, but the and the nature on this slowbro is modest. So that is what you want to do to train up your slowbro. This is the one that I've picked out for this video. And I feel like if you do use it, obviously there are other options that you can have. You can have slack off if you don't want the psychic terrain to have a bit more recovery on there. And like I've said about the item as well, the leftovers or something like that or an expert belt could be an option over the life or but I just prefer having that big damage and having that better chance of being able to one shot the cinderace when I am set up. The next option is going to be armor rouge armor rouge for a few reasons. We've got the item shell bell on here to give you a line of recovery like we like to do with these terror aids. Terror type is going to be psychic for the armor rouge. It is making a bit more sense because it is going to take advantage of that typing advantage that we have over the fighting type cinderace in level 100. Again, it is going to be hyper trained with 31 IVs across the board. EV spread for armor rouge is going to be 252 HP and then 252 special attack. Again, you can optimize that a little bit differently if you want to go more defensive EVs. It is completely up to you what you've been more comfortable with but generally this is quite a consistent EV spread for a terror aid. Flash fire is the ability on armor rouge. It just makes you immune to any sort of fire type attacks that the cinderace is going to throw out. We know the move set that it's got. It's going to have that pyro ball. That is not going to be an issue for you going forward. Then the move set is going to be psychic terrain. Playing a little bit similar to that slow bro. We're going to have the psychic terrain on the field boosting our psychic type attacks. Asset spray is an option as well. A brilliant one. It supports team members as well because you're dropping the special defensive stat on the cinderace every time you use this move. It also hits through the shield when the cinderace does throw that up. Primarily what you want to do is use the asset spray three times. Calm mind a couple of times and then get your psychic terrain up and then start throwing out those expanding force attacks which are going to do extremely huge damage to the cinderace and you do have a good chance of picking up a one shot but it's normally going to take a little bit longer than the slow bro with the armor rouge although a very solid option as well. Again, a modest nature on this armor rouge a bit like the slow bro just taking advantage of that special attack stat to make sure you're getting the damage out that you want on to the field and armor rouge a really solid option and one of the best ones going into this seven star terror raid event and on to the third and final Pokemon probably my favorite out of all three in this video and a really good one that you can not only do solo raids online by yourself the seven star cinderace ones but you can go online and support friends with this particular Pokemon an extremely strong Pokemon option for this is going to be a spathra the psychic type going to have that psychic terror type for it we've given the item twisted spoon you could normally see something like a clear amulet here but because the cinderace doesn't really have any moves that are going to lower your defenses or attack or anything like that it doesn't really feel like it's the most optimal item whereas twisted spoon gives you a boost to your psychic type attacks without any kind of drawbacks as well and you don't need something like the shell bell because we do have an access to the move roost which you'll see in a moment again level 100 again going to be hyper trained 31 IVs across the board for all of its stats going to have the EV spread again of 252 HP and 252 special attack with the remaining put into defense we're going to have the ability opportunist which is an amazing ability especially against the cinderace where it is continually going to use that move bulk up every time it does the opportunist ability will activate and you will gain the same boost as it so meaning that you know when it is boosting its attack up and its defense you'll get in those defense boosts as well meaning that you're going to be able to take those attacks that are increased a lot better with your espathra and you've got the obviously the move set of roost calm mind feather dance and lumina crash so you can use feather dance as an option to reduce the attack stat on that cinderace make sure it's not hitting as hard it's amazing online as well if you're doing this with friends where you can use the feather dance to just reduce the attack stat make sure that it's not picking up knockouts when it otherwise would have done you've got calm mind as well to boost your special attack the special defense boost doesn't really matter too much and you've got that signature move lumina crash which is going to be your main way to do damage on this cinderace and it also reduces the special defense every time you use it on the cinderace meaning that your moves are essentially getting stronger every single turn it works through the shield as well which is amazing so this is one of the reasons why I think espathra is an amazing pokemon and probably a little bit better in my opinion overall than the slow bro because I think the options that it's got to go online and really work as an option to support your fellow pokemon trainers with the feather dance and you've got the ability to also take on board the boost that the cinderace is getting with the opportunist ability it does mean that you're going to be sitting on the field and just stacking up your calm mind boosts and then your lumina crash attacks just to make sure you're going to wear it down and take it down very consistently with this one pokemon so these are the three builds I would say get prepared with at least one of them going into this event this weekend it's going to make it a lot easier for you obviously I think slow bro is probably my overall favorite but I'd say for a more consistent experience if you're doing it solo and you're doing it online then espathra is probably your best option with armor rouge coming in at a close third but it is a very good option nonetheless if you have your own builds though in game that you've already taken part in the last seven star raid event with I would love to hear what you had a lot of success with online obviously there are a lot of builds and nothing is the definitive best one because you can have a lot of options that do have a lot of success in these raids whatever situation you're putting yourself in but I hope you found this video useful and I hope these three builds that we featured today will be very useful for you coming up into the seven star raid for not only getting the cinderace if you haven't already got it but for farming the items which are so valuable and an easy way to get them in your games to make training up and getting money and other things like that a lot easier for you going forward thank you for tuning in if you found today's video useful please drop a like do subscribe to the channel for more Pokemon Scarlet and Violet content and I will see you all in another video very soon until then friends take care of yourselves and bye bye


Hi, this is Kara Sorban and I'm here at Sonnet Sessions with Blackstar and this is my song Way Down. So I follow, so I follow you Way Down. Oh, I doubt you've already missed me by so easy. It's a no-reflection, but you come out of the bad track, and apology wasn't in the wrong.  Oh,